Valid HTML 4.0! Valid CSS!
%%% -*-BibTeX-*-
%%% ====================================================================
%%% BibTeX-file{
%%%     author          = "Nelson H. F. Beebe",
%%%     version         = "1.48",
%%%     date            = "19 August 2023",
%%%     time            = "07:34:53 MDT",
%%%     filename        = "tweb.bib",
%%%     address         = "University of Utah
%%%                        Department of Mathematics, 110 LCB
%%%                        155 S 1400 E RM 233
%%%                        Salt Lake City, UT 84112-0090
%%%                        USA",
%%%     telephone       = "+1 801 581 5254",
%%%     FAX             = "+1 801 581 4148",
%%%     URL             = "http://www.math.utah.edu/~beebe",
%%%     checksum        = "05550 16115 89716 829220",
%%%     email           = "beebe at math.utah.edu, beebe at acm.org,
%%%                        beebe at computer.org (Internet)",
%%%     codetable       = "ISO/ASCII",
%%%     keywords        = "ACM Transactions on the Web (TWEB);
%%%                        bibliography; TWEB",
%%%     license         = "public domain",
%%%     supported       = "yes",
%%%     docstring       = "This is a COMPLETE BibTeX bibliography for
%%%                        ACM Transactions on the Web (TWEB) (CODEN
%%%                        ????, ISSN 1559-1131), covering all journal
%%%                        issues from 2007 -- date.
%%%
%%%                        At version 1.48, the COMPLETE journal
%%%                        coverage looked like this:
%%%
%%%                             2007 (  14)    2013 (  30)    2019 (  20)
%%%                             2008 (  22)    2014 (  19)    2020 (  19)
%%%                             2009 (  14)    2015 (  20)    2021 (  20)
%%%                             2010 (  17)    2016 (  24)    2022 (  21)
%%%                             2011 (  21)    2017 (  25)    2023 (  24)
%%%                             2012 (  18)    2018 (  28)
%%%
%%%                             Article:        356
%%%
%%%                             Total entries:  356
%%%
%%%                        The journal Web page can be found at:
%%%
%%%                            http://www.acm.org/pubs/tweb.html
%%%
%%%                        The journal table of contents page is at:
%%%
%%%                            http://www.acm.org/tweb/
%%%                            http://portal.acm.org/browse_dl.cfm?idx=J1062
%%%
%%%                        Qualified subscribers can retrieve the full
%%%                        text of recent articles in PDF form.
%%%
%%%                        The initial draft was extracted from the ACM
%%%                        Web pages.
%%%
%%%                        ACM copyrights explicitly permit abstracting
%%%                        with credit, so article abstracts, keywords,
%%%                        and subject classifications have been
%%%                        included in this bibliography wherever
%%%                        available.  Article reviews have been
%%%                        omitted, until their copyright status has
%%%                        been clarified.
%%%
%%%                        bibsource keys in the bibliography entries
%%%                        below indicate the entry originally came
%%%                        from the computer science bibliography
%%%                        archive, even though it has likely since
%%%                        been corrected and updated.
%%%
%%%                        URL keys in the bibliography point to
%%%                        World Wide Web locations of additional
%%%                        information about the entry.
%%%
%%%                        BibTeX citation tags are uniformly chosen
%%%                        as name:year:abbrev, where name is the
%%%                        family name of the first author or editor,
%%%                        year is a 4-digit number, and abbrev is a
%%%                        3-letter condensation of important title
%%%                        words. Citation tags were automatically
%%%                        generated by software developed for the
%%%                        BibNet Project.
%%%
%%%                        In this bibliography, entries are sorted in
%%%                        publication order, using ``bibsort -byvolume.''
%%%
%%%                        The checksum field above contains a CRC-16
%%%                        checksum as the first value, followed by the
%%%                        equivalent of the standard UNIX wc (word
%%%                        count) utility output of lines, words, and
%%%                        characters.  This is produced by Robert
%%%                        Solovay's checksum utility."
%%%     }
%%% ====================================================================
@Preamble{"\input bibnames.sty" #
    "\def \TM {${}^{\sc TM}$}"
}

%%% ====================================================================
%%% Acknowledgement abbreviations:
@String{ack-nhfb = "Nelson H. F. Beebe,
                    University of Utah,
                    Department of Mathematics, 110 LCB,
                    155 S 1400 E RM 233,
                    Salt Lake City, UT 84112-0090, USA,
                    Tel: +1 801 581 5254,
                    FAX: +1 801 581 4148,
                    e-mail: \path|beebe@math.utah.edu|,
                            \path|beebe@acm.org|,
                            \path|beebe@computer.org| (Internet),
                    URL: \path|http://www.math.utah.edu/~beebe/|"}

%%% ====================================================================
%%% Journal abbreviations:
@String{j-TWEB                  = "ACM Transactions on the Web (TWEB)"}

%%% ====================================================================
%%% Bibliography entries:
@Article{Ashman:2007:I,
  author =       "Helen Ashman and Arun Iyengar",
  title =        "Introduction",
  journal =      j-TWEB,
  volume =       "1",
  number =       "1",
  pages =        "1:1--1:??",
  month =        may,
  year =         "2007",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1232722.1232723",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:16:53 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "1",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Urgaonkar:2007:AMM,
  author =       "Bhuvan Urgaonkar and Giovanni Pacifici and Prashant
                 Shenoy and Mike Spreitzer and Asser Tantawi",
  title =        "Analytic modeling of multitier {Internet}
                 applications",
  journal =      j-TWEB,
  volume =       "1",
  number =       "1",
  pages =        "2:1--2:??",
  month =        may,
  year =         "2007",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1232722.1232724",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:16:53 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Since many Internet applications employ a multitier
                 architecture, in this article, we focus on the problem
                 of analytically modeling the behavior of such
                 applications. We present a model based on a network of
                 queues where the queues represent different tiers of
                 the application. Our model is sufficiently general to
                 capture (i) the behavior of tiers with significantly
                 different performance characteristics and (ii)
                 application idiosyncrasies such as session-based
                 workloads, tier replication, load imbalances across
                 replicas, and caching at intermediate tiers. We
                 validate our model using real multitier applications
                 running on a Linux server cluster. Our experiments
                 indicate that our model faithfully captures the
                 performance of these applications for a number of
                 workloads and configurations. Furthermore, our model
                 successfully handles a comprehensive range of resource
                 utilization---from 0 to near saturation for the
                 CPU---for two separate tiers. For a variety of
                 scenarios, including those with caching at one of the
                 application tiers, the average response times predicted
                 by our model were within the 95\% confidence intervals
                 of the observed average response times. Our experiments
                 also demonstrate the utility of the model for dynamic
                 capacity provisioning, performance prediction,
                 bottleneck identification, and session policing. In one
                 scenario, where the request arrival rate increased from
                 less than 1500 to nearly 4200 requests/minute, a
                 dynamic provisioning technique employing our model was
                 able to maintain response time targets by increasing
                 the capacity of two of the tiers by factors of 2 and
                 3.5, respectively.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "2",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "analytical model; dynamic provisioning; hosting
                 platform; Internet service; mean-value analysis;
                 performance prediction; policing; queuing theory;
                 session; tier",
}

@Article{Jansen:2007:CES,
  author =       "Bernard J. Jansen",
  title =        "The comparative effectiveness of sponsored and
                 nonsponsored links for {Web} e-commerce queries",
  journal =      j-TWEB,
  volume =       "1",
  number =       "1",
  pages =        "3:1--3:??",
  month =        may,
  year =         "2007",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1232722.1232725",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:16:53 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The predominant business model for Web search engines
                 is sponsored search, which generates billions in yearly
                 revenue. But are sponsored links providing online
                 consumers with relevant choices for products and
                 services? We address this and related issues by
                 investigating the relevance of sponsored and
                 nonsponsored links for e-commerce queries on the major
                 search engines. The results show that average relevance
                 ratings for sponsored and nonsponsored links are
                 practically the same, although the relevance ratings
                 for sponsored links are statistically higher. We used
                 108 ecommerce queries and 8,256 retrieved links for
                 these queries from three major Web search engines:
                 Yahoo!, Google, and MSN. In addition to relevance
                 measures, we qualitatively analyzed the e-commerce
                 queries, deriving five categorizations of underlying
                 information needs. Product-specific queries are the
                 most prevalent (48\%). Title (62\%) and summary (33\%)
                 are the primary basis for evaluating sponsored links
                 with URL a distant third (2\%). To gauge the
                 effectiveness of sponsored search campaigns, we
                 analyzed the sponsored links from various viewpoints.
                 It appears that links from organizations with large
                 sponsored search campaigns are more relevant than the
                 average sponsored link. We discuss the implications for
                 Web search engines and sponsored search as a long-term
                 business model and as a mechanism for finding relevant
                 information for searchers.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "3",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "e-commerce searching; sponsored links; sponsored
                 results; sponsored search; Web search engines; Web
                 searching",
}

@Article{Church:2007:MIA,
  author =       "Karen Church and Barry Smyth and Paul Cotter and Keith
                 Bradley",
  title =        "Mobile information access: a study of emerging
                 search behavior on the mobile {Internet}",
  journal =      j-TWEB,
  volume =       "1",
  number =       "1",
  pages =        "4:1--4:??",
  month =        may,
  year =         "2007",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1232722.1232726",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:16:53 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "It is likely that mobile phones will soon come to
                 rival more traditional devices as the primary platform
                 for information access. Consequently, it is important
                 to understand the emerging information access behavior
                 of mobile Internet (MI) users especially in relation to
                 their use of mobile handsets for information browsing
                 and query-based search. In this article, we describe
                 the results of a recent analysis of the MI habits of
                 more than 600,000 European MI users, with a particular
                 emphasis on the emerging interest in mobile search. We
                 consider a range of factors including whether there are
                 key differences between browsing and search behavior on
                 the MI compared to the Web. We highlight how browsing
                 continues to dominate mobile information access, but go
                 on to show how search is becoming an increasingly
                 popular information access alternative especially in
                 relation to certain types of mobile handsets and
                 information needs. Moreover, we show that sessions
                 involving search tend to be longer and more data-rich
                 than those that do not involve search. We also look at
                 the type of queries used during mobile search and the
                 way that these queries tend to be modified during the
                 course of a mobile search session. Finally we examine
                 the overlap among mobile search queries and the
                 different topics mobile users are interested in.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "4",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "log analysis; Mobile browsing; mobile Internet; mobile
                 search",
}

@Article{Leskovec:2007:DVM,
  author =       "Jure Leskovec and Lada A. Adamic and Bernardo A.
                 Huberman",
  title =        "The dynamics of viral marketing",
  journal =      j-TWEB,
  volume =       "1",
  number =       "1",
  pages =        "5:1--5:??",
  month =        may,
  year =         "2007",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1232722.1232727",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:16:53 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "We present an analysis of a person-to-person
                 recommendation network, consisting of 4 million people
                 who made 16 million recommendations on half a million
                 products. We observe the propagation of recommendations
                 and the cascade sizes, which we explain by a simple
                 stochastic model. We analyze how user behavior varies
                 within user communities defined by a recommendation
                 network. Product purchases follow a `long tail' where a
                 significant share of purchases belongs to rarely sold
                 items. We establish how the recommendation network
                 grows over time and how effective it is from the
                 viewpoint of the sender and receiver of the
                 recommendations. While on average recommendations are
                 not very effective at inducing purchases and do not
                 spread very far, we present a model that successfully
                 identifies communities, product, and pricing categories
                 for which viral marketing seems to be very effective.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "5",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "e-commerce; long tail; network analysis; recommender
                 systems; Viral marketing; word-of-mouth",
}

@Article{Yu:2007:EAW,
  author =       "Tao Yu and Yue Zhang and Kwei-Jay Lin",
  title =        "Efficient algorithms for {Web} services selection with
                 end-to-end {QoS} constraints",
  journal =      j-TWEB,
  volume =       "1",
  number =       "1",
  pages =        "6:1--6:??",
  month =        may,
  year =         "2007",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1232722.1232728",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:16:53 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Service-Oriented Architecture (SOA) provides a
                 flexible framework for service composition. Using
                 standard-based protocols (such as SOAP and WSDL),
                 composite services can be constructed by integrating
                 atomic services developed independently. Algorithms are
                 needed to select service components with various QoS
                 levels according to some application-dependent
                 performance requirements. We design a broker-based
                 architecture to facilitate the selection of QoS-based
                 services. The objective of service selection is to
                 maximize an application-specific utility function under
                 the end-to-end QoS constraints. The problem is modeled
                 in two ways: the combinatorial model and the graph
                 model. The combinatorial model defines the problem as a
                 multidimension multichoice 0-1 knapsack problem (MMKP).
                 The graph model defines the problem as a
                 multiconstraint optimal path (MCOP) problem. Efficient
                 heuristic algorithms for service processes of different
                 composition structures are presented in this article
                 and their performances are studied by simulations. We
                 also compare the pros and cons between the two
                 models.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "6",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "End-to-end QoS; service composition; service oriented
                 architecture (SOA); service selection; Web services",
}

@Article{Dubinko:2007:VTT,
  author =       "Micah Dubinko and Ravi Kumar and Joseph Magnani and
                 Jasmine Novak and Prabhakar Raghavan and Andrew
                 Tomkins",
  title =        "Visualizing tags over time",
  journal =      j-TWEB,
  volume =       "1",
  number =       "2",
  pages =        "7:1--7:??",
  month =        aug,
  year =         "2007",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1255438.1255439",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:17:06 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "We consider the problem of visualizing the evolution
                 of tags within the Flickr (flickr.com) online image
                 sharing community. Any user of the Flickr service may
                 append a tag to any photo in the system. Over the past
                 year, users have on average added over a million tags
                 each week. Understanding the evolution of these tags
                 over time is therefore a challenging task. We present a
                 new approach based on a characterization of the most
                 interesting tags associated with a sliding interval of
                 time. An animation provided via Flash in a Web browser
                 allows the user to observe and interact with the
                 interesting tags as they evolve over time.\par

                 New algorithms and data structures are required to
                 support the efficient generation of this visualization.
                 We combine a novel solution to an interval covering
                 problem with extensions to previous work on score
                 aggregation in order to create an efficient backend
                 system capable of producing visualizations at arbitrary
                 scales on this large dataset in real time.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "7",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "Flickr; interval covering; tags; temporal evolution;
                 visualization",
}

@Article{Mohan:2007:SPC,
  author =       "Bharath Kumar Mohan and Benjamin J. Keller and Naren
                 Ramakrishnan",
  title =        "Scouts, promoters, and connectors: {The} roles of
                 ratings in nearest-neighbor collaborative filtering",
  journal =      j-TWEB,
  volume =       "1",
  number =       "2",
  pages =        "8:1--8:??",
  month =        aug,
  year =         "2007",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1255438.1255440",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:17:06 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Recommender systems aggregate individual user ratings
                 into predictions of products or services that might
                 interest visitors. The quality of this aggregation
                 process crucially affects the user experience and hence
                 the effectiveness of recommenders in e-commerce. We
                 present a characterization of nearest-neighbor
                 collaborative filtering that allows us to disaggregate
                 global recommender performance measures into
                 contributions made by each individual rating. In
                 particular, we formulate three roles--- {\em scouts},
                 {\em promoters}, and {\em connectors\/} ---that capture
                 how users receive recommendations, how items get
                 recommended, and how ratings of these two types are
                 themselves connected, respectively. These roles find
                 direct uses in improving recommendations for users, in
                 better targeting of items and, most importantly, in
                 helping monitor the health of the system as a whole.
                 For instance, they can be used to track the evolution
                 of neighborhoods, to identify rating subspaces that do
                 not contribute (or contribute negatively) to system
                 performance, to enumerate users who are in danger of
                 leaving, and to assess the susceptibility of the system
                 to attacks such as shilling. We argue that the three
                 rating roles presented here provide broad primitives to
                 manage a recommender system and its community.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "8",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "collaborative filtering; connectors; neighborhoods;
                 promoters; Recommender systems; scouts; user-based and
                 item-based algorithms",
}

@Article{Rogers:2007:EPB,
  author =       "Alex Rogers and Esther David and Nicholas R. Jennings
                 and Jeremy Schiff",
  title =        "The effects of proxy bidding and minimum bid
                 increments within {eBay} auctions",
  journal =      j-TWEB,
  volume =       "1",
  number =       "2",
  pages =        "9:1--9:??",
  month =        aug,
  year =         "2007",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1255438.1255441",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:17:06 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "We present a mathematical model of the eBay auction
                 protocol and perform a detailed analysis of the effects
                 that the eBay proxy bidding system and the minimum bid
                 increment have on the auction properties. We first
                 consider the revenue of the auction, and we show
                 analytically that when two bidders with independent
                 private valuations use the eBay proxy bidding system
                 there exists an optimal value for the minimum bid
                 increment at which the auctioneer's revenue is
                 maximized. We then consider the sequential way in which
                 bids are placed within the auction, and we show
                 analytically that independent of assumptions regarding
                 the bidders' valuation distribution or bidding strategy
                 the number of visible bids placed is related to the
                 logarithm of the number of potential bidders. Thus, in
                 many cases, it is only a minority of the potential
                 bidders that are able to submit bids and are visible in
                 the auction bid history (despite the fact that the
                 other hidden bidders are still effectively competing
                 for the item). Furthermore, we show through simulation
                 that the minimum bid increment also introduces an
                 inefficiency to the auction, whereby a bidder who
                 enters the auction late may find that its valuation is
                 insufficient to allow them to advance the current bid
                 by the minimum bid increment despite them actually
                 having the highest valuation for the item. Finally, we
                 use these results to consider appropriate strategies
                 for bidders within real world eBay auctions. We show
                 that while last-minute bidding (sniping) is an
                 effective strategy against bidders engaging in
                 incremental bidding (and against those with common
                 values), in general, delaying bidding is
                 disadvantageous even if delayed bids are sure to be
                 received before the auction closes. Thus, when several
                 bidders submit last-minute bids, we show that rather
                 than seeking to bid as late as possible, a bidder
                 should try to be the first sniper to bid (i.e., it
                 should ``snipe before the snipers'').",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "9",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "bid increment; electronic commerce; Online auctions;
                 proxy bidding; sniping",
}

@Article{Serrano:2007:DSW,
  author =       "M. {\'A}ngeles Serrano and Ana Maguitman and
                 Mari{\'a}n Bogu{\~n}{\'a} and Santo Fortunato and
                 Alessandro Vespignani",
  title =        "Decoding the structure of the {WWW}: a comparative
                 analysis of {Web} crawls",
  journal =      j-TWEB,
  volume =       "1",
  number =       "2",
  pages =        "10:1--10:??",
  month =        aug,
  year =         "2007",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1255438.1255442",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:17:06 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The understanding of the immense and intricate
                 topological structure of the World Wide Web (WWW) is a
                 major scientific and technological challenge. This has
                 been recently tackled by characterizing the properties
                 of its representative graphs, in which vertices and
                 directed edges are identified with Web pages and
                 hyperlinks, respectively. Data gathered in large-scale
                 crawls have been analyzed by several groups resulting
                 in a general picture of the WWW that encompasses many
                 of the complex properties typical of rapidly evolving
                 networks. In this article, we report a detailed
                 statistical analysis of the topological properties of
                 four different WWW graphs obtained with different
                 crawlers. We find that, despite the very large size of
                 the samples, the statistical measures characterizing
                 these graphs differ quantitatively, and in some cases
                 qualitatively, depending on the domain analyzed and the
                 crawl used for gathering the data. This spurs the issue
                 of the presence of sampling biases and structural
                 differences of Web crawls that might induce properties
                 not representative of the actual global underlying
                 graph. In short, the stability of the widely accepted
                 statistical description of the Web is called into
                 question. In order to provide a more accurate
                 characterization of the Web graph, we study statistical
                 measures beyond the degree distribution, such as
                 degree-degree correlation functions or the statistics
                 of reciprocal connections. The latter appears to
                 enclose the relevant correlations of the WWW graph and
                 carry most of the topological information of the Web.
                 The analysis of this quantity is also of major interest
                 in relation to the navigability and searchability of
                 the Web.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "10",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "crawler biases; statistical analysis; Web graph
                 structure; Web measurement",
}

@Article{Reis:2007:BVD,
  author =       "Charles Reis and John Dunagan and Helen J. Wang and
                 Opher Dubrovsky and Saher Esmeir",
  title =        "{BrowserShield}: {Vulnerability}-driven filtering of
                 dynamic {HTML}",
  journal =      j-TWEB,
  volume =       "1",
  number =       "3",
  pages =        "11:1--11:??",
  month =        sep,
  year =         "2007",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1281480.1281481",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:17:14 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Vulnerability-driven filtering of network data can
                 offer a fast and easy-to-deploy alternative or
                 intermediary to software patching, as exemplified in
                 Shield [Wang et al. 2004]. In this article, we take
                 Shield's vision to a new domain, inspecting and
                 cleansing not just static content, but also dynamic
                 content. The dynamic content we target is the dynamic
                 HTML in Web pages, which have become a popular vector
                 for attacks. The key challenge in filtering dynamic
                 HTML is that it is undecidable to statically determine
                 whether an embedded script will exploit the browser at
                 runtime. We avoid this undecidability problem by
                 rewriting web pages and any embedded scripts into safe
                 equivalents, inserting checks so that the filtering is
                 done at runtime. The rewritten pages contain logic for
                 recursively applying runtime checks to dynamically
                 generated or modified web content, based on known
                 vulnerabilities. We have built and evaluated {\em
                 BrowserShield}, a general framework that performs this
                 dynamic instrumentation of embedded scripts, and that
                 admits policies for customized runtime actions like
                 vulnerability-driven filtering. We also explore other
                 applications on top of BrowserShield.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "11",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "code rewriting; JavaScript; vulnerability; Web
                 browser",
}

@Article{Sun:2007:MDW,
  author =       "Zan Sun and Jalal Mahmud and I. V. Ramakrishnan and
                 Saikat Mukherjee",
  title =        "Model-directed {Web} transactions under constrained
                 modalities",
  journal =      j-TWEB,
  volume =       "1",
  number =       "3",
  pages =        "12:1--12:??",
  month =        sep,
  year =         "2007",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1281480.1281482",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:17:14 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Online transactions (e.g., buying a book on the Web)
                 typically involve a number of steps spanning several
                 pages. Conducting such transactions under constrained
                 interaction modalities as exemplified by small screen
                 handhelds or interactive speech interfaces --- the
                 primary mode of communication for visually impaired
                 individuals --- is a strenuous, fatigue-inducing
                 activity. But usually one needs to browse only a small
                 fragment of a Web page to perform a transactional step
                 such as a form fillout, selecting an item from a search
                 results list, and so on. We exploit this observation to
                 develop an automata-based process model that delivers
                 only the ``relevant'' page fragments at each
                 transactional step, thereby reducing information
                 overload on such narrow interaction bandwidths. We
                 realize this model by coupling techniques from content
                 analysis of Web documents, automata learning and
                 statistical classification. The process model and
                 associated techniques have been incorporated into
                 Guide-O, a prototype system that facilitates online
                 transactions using speech/keyboard interface
                 (Guide-O-Speech), or with limited-display size
                 handhelds (Guide-O-Mobile). Performance of Guide-O and
                 its user experience are reported.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "12",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "assistive device; content adaption; Web transaction",
}

@Article{Sharman:2007:CAD,
  author =       "Raj Sharman and Shiva Shankar Ramanna and Ram Ramesh
                 and Ram Gopal",
  title =        "Cache architecture for on-demand streaming on the
                 {Web}",
  journal =      j-TWEB,
  volume =       "1",
  number =       "3",
  pages =        "13:1--13:??",
  month =        sep,
  year =         "2007",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1281480.1281483",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:17:14 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "On-demand streaming from a remote server through
                 best-effort Internet poses several challenges because
                 of network losses and variable delays. The primary
                 technique used to improve the quality of distributed
                 content service is replication. In the context of the
                 Internet, Web caching is the traditional mechanism that
                 is used. In this article we develop a new staged
                 delivery model for a distributed architecture in which
                 video is streamed from remote servers to edge caches
                 where the video is buffered and then streamed to the
                 client through a last-mile connection. The model uses a
                 novel revolving indexed cache buffer management
                 mechanism at the edge cache and employs selective
                 retransmissions of lost packets between the remote and
                 edge cache for a best-effort recovery of the losses.
                 The new Web cache buffer management scheme includes a
                 dynamic adjustment of cache buffer parameters based on
                 network conditions. In addition, performance of buffer
                 management and retransmission policies at the edge
                 cache is modeled and assessed using a probabilistic
                 analysis of the streaming process as well as system
                 simulations. The influence of different endogenous
                 control parameters on the quality of stream received by
                 the client is studied. Calibration curves on the QoS
                 metrics for different network conditions have been
                 obtained using simulations. Edge cache management can
                 be done using these calibration curves. ISPs can make
                 use of calibration curves to set the values of the
                 endogenous control parameters for specific QoS in
                 real-time streaming operations based on network
                 conditions. A methodology to benchmark transmission
                 characteristics using real-time traffic data is
                 developed to enable effective decision making on edge
                 cache buffer allocation and management strategies.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "13",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "buffering; edge cache; on-demand streaming; quality of
                 service; selective retransmissions; Web caching",
}

@Article{Zdun:2007:MPD,
  author =       "Uwe Zdun and Carsten Hentrich and Schahram Dustdar",
  title =        "Modeling process-driven and service-oriented
                 architectures using patterns and pattern primitives",
  journal =      j-TWEB,
  volume =       "1",
  number =       "3",
  pages =        "14:1--14:??",
  month =        sep,
  year =         "2007",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1281480.1281484",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:17:14 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Service-oriented architectures are increasingly used
                 in the context of business processes. However, the
                 proven practices for process-oriented integration of
                 services are not well documented yet. In addition,
                 modeling approaches for the integration of processes
                 and services are neither mature nor do they exactly
                 reflect the proven practices. In this article, we
                 propose a pattern language for process-oriented
                 integration of services to describe the proven
                 practices. Our main contribution is a modeling concept
                 based on pattern primitives for these patterns. A
                 pattern primitive is a fundamental, precisely specified
                 modeling element that represents a pattern. We present
                 a catalog of pattern primitives that are precisely
                 modeled using OCL constraints and map these primitives
                 to the patterns in the pattern language of
                 process-oriented integration of services. We also
                 present a model validation tool that we have developed
                 to support modeling the process-oriented integration of
                 services, and an industrial case study in which we have
                 applied our results.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "14",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "middleware; Service-oriented architecture; software
                 patterns",
}

@Article{Najork:2008:ISS,
  author =       "Marc Najork and Brian D. Davison",
  title =        "Introduction to special section on adversarial issues
                 in {Web} search",
  journal =      j-TWEB,
  volume =       "2",
  number =       "1",
  pages =        "1:1--1:??",
  month =        feb,
  year =         "2008",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1326561.1326562",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:17:25 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "1",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Becchetti:2008:LAW,
  author =       "Luca Becchetti and Carlos Castillo and Debora Donato
                 and Ricardo Baeza-Yates and Stefano Leonardi",
  title =        "Link analysis for {Web} spam detection",
  journal =      j-TWEB,
  volume =       "2",
  number =       "1",
  pages =        "2:1--2:??",
  month =        feb,
  year =         "2008",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1326561.1326563",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:17:25 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "We propose link-based techniques for automatic
                 detection of Web spam, a term referring to pages which
                 use deceptive techniques to obtain undeservedly high
                 scores in search engines. The use of Web spam is
                 widespread and difficult to solve, mostly due to the
                 large size of the Web which means that, in practice,
                 many algorithms are infeasible.\par

                 We perform a statistical analysis of a large collection
                 of Web pages. In particular, we compute statistics of
                 the links in the vicinity of every Web page applying
                 rank propagation and probabilistic counting over the
                 entire Web graph in a scalable way. These statistical
                 features are used to build Web spam classifiers which
                 only consider the link structure of the Web, regardless
                 of page contents. We then present a study of the
                 performance of each of the classifiers alone, as well
                 as their combined performance, by testing them over a
                 large collection of Web link spam. After tenfold
                 cross-validation, our best classifiers have a
                 performance comparable to that of state-of-the-art spam
                 classifiers that use content attributes, but are
                 orthogonal to content-based methods.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "2",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "adversarial information retrieval; Link analysis",
}

@Article{Urvoy:2008:TWS,
  author =       "Tanguy Urvoy and Emmanuel Chauveau and Pascal Filoche
                 and Thomas Lavergne",
  title =        "Tracking {Web} spam with {HTML} style similarities",
  journal =      j-TWEB,
  volume =       "2",
  number =       "1",
  pages =        "3:1--3:??",
  month =        feb,
  year =         "2008",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1326561.1326564",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:17:25 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Automatically generated content is ubiquitous in the
                 web: dynamic sites built using the three-tier paradigm
                 are good examples (e.g., commercial sites, blogs and
                 other sites edited using web authoring software), as
                 well as less legitimate spamdexing attempts (e.g., link
                 farms, faked directories).\par

                 Those pages built using the same generating method
                 (template or script) share a common ``look and feel''
                 that is not easily detected by common text
                 classification methods, but is more related to
                 stylometry.\par

                 In this work we study and compare several HTML style
                 similarity measures based on both textual and
                 extra-textual features in HTML source code. We also
                 propose a flexible algorithm to cluster a large
                 collection of documents according to these measures.
                 Since the proposed algorithm is based on locality
                 sensitive hashing (LSH), we first review this
                 technique.\par

                 We then describe how to use the HTML style similarity
                 clusters to pinpoint dubious pages and enhance the
                 quality of spam classifiers. We present an evaluation
                 of our algorithm on the WEBSPAM-UK2006 dataset.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "3",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "Clustering; document similarity; search engine spam;
                 stylometry; templates identification",
}

@Article{Lin:2008:DST,
  author =       "Yu-Ru Lin and Hari Sundaram and Yun Chi and Junichi
                 Tatemura and Belle L. Tseng",
  title =        "Detecting splogs via temporal dynamics using
                 self-similarity analysis",
  journal =      j-TWEB,
  volume =       "2",
  number =       "1",
  pages =        "4:1--4:??",
  month =        feb,
  year =         "2008",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1326561.1326565",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:17:25 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "This article addresses the problem of spam blog
                 (splog) detection using temporal and structural
                 regularity of content, post time and links. Splogs are
                 undesirable blogs meant to attract search engine
                 traffic, used solely for promoting affiliate sites.
                 Blogs represent popular online media, and splogs not
                 only degrade the quality of search engine results, but
                 also waste network resources. The splog detection
                 problem is made difficult due to the lack of stable
                 content descriptors.\par

                 We have developed a new technique for detecting splogs,
                 based on the observation that a blog is a dynamic,
                 growing sequence of entries (or posts) rather than a
                 collection of individual pages. In our approach, splogs
                 are recognized by their temporal characteristics and
                 content. There are three key ideas in our splog
                 detection framework. (a) We represent the blog temporal
                 dynamics using self-similarity matrices defined on the
                 histogram intersection similarity measure of the time,
                 content, and link attributes of posts, to investigate
                 the temporal changes of the post sequence. (b) We study
                 the blog temporal characteristics using a visual
                 representation derived from the self-similarity
                 measures. The visual signature reveals correlation
                 between attributes and posts, depending on the type of
                 blogs (normal blogs and splogs). (c) We propose two
                 types of novel temporal features to capture the splog
                 temporal characteristics. In our splog detector, these
                 novel features are combined with content based
                 features. We extract a content based feature vector
                 from blog home pages as well as from different parts of
                 the blog. The dimensionality of the feature vector is
                 reduced by Fisher linear discriminant analysis. We have
                 tested an SVM-based splog detector using proposed
                 features on real world datasets, with appreciable
                 results (90\% accuracy).",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "4",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "Blogs; regularity; self-similarity; spam; splog
                 detection; temporal dynamics; topology",
}

@Article{Weinreich:2008:QAE,
  author =       "Harald Weinreich and Hartmut Obendorf and Eelco Herder
                 and Matthias Mayer",
  title =        "Not quite the average: an empirical study of {Web}
                 use",
  journal =      j-TWEB,
  volume =       "2",
  number =       "1",
  pages =        "5:1--5:??",
  month =        feb,
  year =         "2008",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1326561.1326566",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:17:25 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "In the past decade, the World Wide Web has been
                 subject to dramatic changes. Web sites have evolved
                 from static information resources to dynamic and
                 interactive applications that are used for a broad
                 scope of activities on a daily basis. To examine the
                 consequences of these changes on user behavior, we
                 conducted a long-term client-side Web usage study with
                 twenty-five participants. This report presents results
                 of this study and compares the user behavior with
                 previous long-term browser usage studies, which range
                 in age from seven to thirteen years. Based on the
                 empirical data and the interview results, various
                 implications for the interface design of browsers and
                 Web sites are discussed.\par

                 A major finding is the decreasing prominence of
                 backtracking in Web navigation. This can largely be
                 attributed to the increasing importance of dynamic,
                 service-oriented Web sites. Users do not navigate on
                 these sites searching for information, but rather
                 interact with an online application to complete certain
                 tasks. Furthermore, the usage of multiple windows and
                 tabs has partly replaced back button usage, posing new
                 challenges for user orientation and backtracking. We
                 found that Web browsing is a rapid activity even for
                 pages with substantial content, which calls for page
                 designs that allow for cursory reading. Click maps
                 provide additional information on how users interact
                 with the Web on page level. Finally, substantial
                 differences were observed between users, and
                 characteristic usage patterns for different types of
                 Web sites emphasize the need for more adaptive and
                 customizable Web browsers.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "5",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "browser interfaces; hypertext; Navigation; usability;
                 user study; Web; web browsing; web design; WWW",
}

@Article{Yu:2008:FWS,
  author =       "Qi Yu and Athman Bouguettaya",
  title =        "Framework for {Web} service query algebra and
                 optimization",
  journal =      j-TWEB,
  volume =       "2",
  number =       "1",
  pages =        "6:1--6:??",
  month =        feb,
  year =         "2008",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1326561.1326567",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:17:25 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "We present a query algebra that supports optimized
                 access of Web services through service-oriented
                 queries. The service query algebra is defined based on
                 a formal service model that provides a high-level
                 abstraction of Web services across an application
                 domain. The algebra defines a set of algebraic
                 operators. Algebraic service queries can be formulated
                 using these operators. This allows users to query their
                 desired services based on both functionality and
                 quality. We provide the implementation of each
                 algebraic operator. This enables the generation of
                 Service Execution Plans (SEPs) that can be used by
                 users to directly access services. We present an
                 optimization algorithm by extending the Dynamic
                 Programming (DP) approach to efficiently select the
                 SEPs with the best user-desired quality. The
                 experimental study validates the proposed algorithm by
                 demonstrating significant performance improvement
                 compared with the traditional DP approach.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "6",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "query optimization; service oriented computing;
                 service query; Web service",
}

@Article{Aleman-Meza:2008:SSA,
  author =       "Boanerges Aleman-Meza and Meenakshi Nagarajan and Li
                 Ding and Amit Sheth and I. Budak Arpinar and Anupam
                 Joshi and Tim Finin",
  title =        "Scalable semantic analytics on social networks for
                 addressing the problem of conflict of interest
                 detection",
  journal =      j-TWEB,
  volume =       "2",
  number =       "1",
  pages =        "7:1--7:??",
  month =        feb,
  year =         "2008",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1326561.1326568",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:17:25 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "In this article, we demonstrate the applicability of
                 semantic techniques for detection of Conflict of
                 Interest (COI). We explain the common challenges
                 involved in building scalable Semantic Web
                 applications, in particular those addressing
                 connecting-the-dots problems. We describe in detail the
                 challenges involved in two important aspects on
                 building Semantic Web applications, namely, data
                 acquisition and entity disambiguation (or reference
                 reconciliation). We extend upon our previous work where
                 we integrated the collaborative network of a subset of
                 DBLP researchers with persons in a Friend-of-a-Friend
                 social network (FOAF). Our method finds the connections
                 between people, measures collaboration strength, and
                 includes heuristics that use friendship/affiliation
                 information to provide an estimate of potential COI in
                 a peer-review scenario. Evaluations are presented by
                 measuring what could have been the COI between accepted
                 papers in various conference tracks and their
                 respective program committee members. The experimental
                 results demonstrate that scalability can be achieved by
                 using a dataset of over 3 million entities (all
                 bibliographic data from DBLP and a large collection of
                 FOAF documents).",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "7",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "conflict of interest; data fusion; DBLP; entity
                 disambiguation; ontologies; peer review process; RDF;
                 semantic analytics; semantic associations; Semantic
                 Web; social networks; swetoDblp",
}

@Article{Gmach:2008:AQS,
  author =       "Daniel Gmach and Stefan Krompass and Andreas Scholz
                 and Martin Wimmer and Alfons Kemper",
  title =        "Adaptive quality of service management for enterprise
                 services",
  journal =      j-TWEB,
  volume =       "2",
  number =       "1",
  pages =        "8:1--8:??",
  month =        feb,
  year =         "2008",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1326561.1326569",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:17:25 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "In the past, enterprise resource planning systems were
                 designed as monolithic software systems running on
                 centralized mainframes. Today, these systems are
                 (re-)designed as a repository of enterprise services
                 that are distributed throughout the available computing
                 infrastructure. These service oriented architectures
                 (SOAs) require advanced automatic and adaptive
                 management concepts in order to achieve a high quality
                 of service level in terms of, for example,
                 availability, responsiveness, and throughput. The
                 adaptive management has to allocate service instances
                 to computing resources, adapt the resource allocation
                 to unforeseen load fluctuations, and intelligently
                 schedule individual requests to guarantee negotiated
                 service level agreements (SLAs). Our AutoGlobe platform
                 provides such a comprehensive adaptive service
                 management comprising\par

                 --- static service-to-server allocation based on
                 automatically detected service utilization
                 patterns,\par

                 --- adaptive service management based on a fuzzy
                 controller that remedies exceptional situations by
                 automatically initiating, for example, service
                 migration, service replication (scale-out), and\par

                 --- adaptive scheduling of individual service requests
                 that prioritizes requests depending on the current
                 degree of service level conformance.\par

                 All three complementary control components are
                 described in detail, and their effectiveness is
                 analyzed by means of realistic business application
                 scenarios.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "8",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "fuzzy controller; Quality of service; workload
                 characterization",
}

@Article{Yang:2008:DGN,
  author =       "Bo Yang and Jiming Liu",
  title =        "Discovering global network communities based on local
                 centralities",
  journal =      j-TWEB,
  volume =       "2",
  number =       "1",
  pages =        "9:1--9:??",
  month =        feb,
  year =         "2008",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1326561.1326570",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:17:25 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "One of the central problems in studying and
                 understanding complex networks, such as online social
                 networks or World Wide Web, is to discover hidden,
                 either physically (e.g., interactions or hyperlinks) or
                 logically (e.g., profiles or semantics) well-defined
                 topological structures. From a practical point of view,
                 a good example of such structures would be so-called
                 network communities. Earlier studies have introduced
                 various formulations as well as methods for the problem
                 of identifying or extracting communities. While each of
                 them has pros and cons as far as the effectiveness and
                 efficiency are concerned, almost none of them has
                 explicitly dealt with the potential relationship
                 between the global topological property of a network
                 and the local property of individual nodes. In order to
                 study this problem, this paper presents a new
                 algorithm, called ICS, which aims to discover natural
                 network communities by inferring from the local
                 information of nodes inherently hidden in networks
                 based on a new centrality, that is, clustering
                 centrality, which is a generalization of eigenvector
                 centrality. As compared with existing methods, our
                 method runs efficiently with a good clustering
                 performance. Additionally, it is insensitive to its
                 built-in parameters and prior knowledge.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "9",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "centrality; community mining; Complex network; graph
                 theory; World Wide Web",
}

@Article{Dustdar:2008:ISI,
  author =       "Schahram Dustdar and Bernd J. Kr{\"a}mer",
  title =        "Introduction to special issue on service oriented
                 computing {(SOC)}",
  journal =      j-TWEB,
  volume =       "2",
  number =       "2",
  pages =        "10:1--10:??",
  month =        apr,
  year =         "2008",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1346337.1346338",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:17:47 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "10",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Belhajjame:2008:AAW,
  author =       "Khalid Belhajjame and Suzanne M. Embury and Norman W.
                 Paton and Robert Stevens and Carole A. Goble",
  title =        "Automatic annotation of {Web} services based on
                 workflow definitions",
  journal =      j-TWEB,
  volume =       "2",
  number =       "2",
  pages =        "11:1--11:??",
  month =        apr,
  year =         "2008",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1346237.1346239",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:17:47 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Semantic annotations of web services can support the
                 effective and efficient discovery of services, and
                 guide their composition into workflows. At present,
                 however, the practical utility of such annotations is
                 limited by the small number of service annotations
                 available for general use. Manual annotation of
                 services is a time consuming and thus expensive task,
                 so some means are required by which services can be
                 automatically (or semi-automatically) annotated. In
                 this paper, we show how information can be inferred
                 about the semantics of operation parameters based on
                 their connections to other (annotated) operation
                 parameters within tried-and-tested workflows. Because
                 the data links in the workflows do not necessarily
                 contain every possible connection of compatible
                 parameters, we can infer only constraints on the
                 semantics of parameters. We show that despite their
                 imprecise nature these so-called {\em loose
                 annotations\/} are still of value in supporting the
                 manual annotation task, inspecting workflows and
                 discovering services. We also show that derived
                 annotations for already annotated parameters are
                 useful. By comparing existing and newly derived
                 annotations of operation parameters, we can support the
                 detection of errors in existing annotations, the
                 ontology used for annotation and in workflows. The
                 derivation mechanism has been implemented, and its
                 practical applicability for inferring new annotations
                 has been established through an experimental
                 evaluation. The usefulness of the derived annotations
                 is also demonstrated.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "11",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "automatic annotation; ontologies; semantic
                 annotations; Semantic web services; workflows",
}

@Article{Elgedawy:2008:CAH,
  author =       "Islam Elgedawy and Zahir Tari and James A. Thom",
  title =        "Correctness-aware high-level functional matching
                 approaches for semantic {Web} services",
  journal =      j-TWEB,
  volume =       "2",
  number =       "2",
  pages =        "12:1--12:??",
  month =        apr,
  year =         "2008",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1346237.1346240",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:17:47 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Service matching approaches trade precision for
                 recall, creating the need for users to choose the
                 correct services, which obviously is a major obstacle
                 for automating the service discovery and aggregation
                 processes. Our approach to overcome this problem, is to
                 eliminate the appearance of false positives by
                 returning only the correct services. As different users
                 have different semantics for what is correct, we argue
                 that the correctness of the matching results must be
                 determined according to the achievement of users'
                 goals: that only services achieving users' goals are
                 considered correct. To determine such correctness, we
                 argue that the matching process should be based
                 primarily on the high-level functional specifications
                 (namely goals, achievement contexts, and external
                 behaviors). In this article, we propose models, data
                 structures, algorithms, and theorems required to
                 correctly match such specifications. We propose a model
                 called $ G^+ $, to capture such specifications, for
                 both services and users, in a machine-understandable
                 format. We propose a data structure, called a Concepts
                 Substitutability Graph (CSG), to capture the
                 substitution semantics of application domain concepts
                 in a context-based manner, in order to determine the
                 semantic-preserving mapping transformations required to
                 match different {\em G\/}$^+$ models. We also propose a
                 behavior matching approach that is able to match states
                 in an m-to-n manner, such that behavior models with
                 different numbers of state transitions can be matched.
                 Finally, we show how services are matched and
                 aggregated according to their $ G^+ $ models. Results
                 of supporting experiments demonstrate the advantages of
                 the proposed service matching approaches.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "12",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "High-level functional matching; semantic Web services;
                 service aggregation",
}

@Article{Ryu:2008:SDE,
  author =       "Seung Hwan Ryu and Fabio Casati and Halvard Skogsrud
                 and Boualem Benatallah and R{\'e}gis Saint-Paul",
  title =        "Supporting the dynamic evolution of {Web} service
                 protocols in service-oriented architectures",
  journal =      j-TWEB,
  volume =       "2",
  number =       "2",
  pages =        "13:1--13:??",
  month =        apr,
  year =         "2008",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1346237.1346241",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:17:47 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "In service-oriented architectures, everything is a
                 service and everyone is a service provider. Web
                 services (or simply services) are loosely coupled
                 software components that are published, discovered, and
                 invoked across the Web. As the use of Web service
                 grows, in order to correctly interact with them, it is
                 important to understand the business protocols that
                 provide clients with the information on how to interact
                 with services. In dynamic Web service environments,
                 service providers need to constantly adapt their
                 business protocols for reflecting the restrictions and
                 requirements proposed by new applications, new business
                 strategies, and new laws, or for fixing problems found
                 in the protocol definition. However, the effective
                 management of such a protocol evolution raises critical
                 problems: one of the most critical issues is how to
                 handle instances running under the old protocol when it
                 has been changed. Simple solutions, such as aborting
                 them or allowing them to continue to run according to
                 the old protocol, can be considered, but they are
                 inapplicable for many reasons (for example, the loss of
                 work already done and the critical nature of work). In
                 this article, we present a framework that supports
                 service managers in managing the business protocol
                 evolution by providing several features, such as a
                 variety of protocol change impact analyses
                 automatically determining which ongoing instances can
                 be migrated to the new version of protocol, and data
                 mining techniques inferring interaction patterns used
                 for classifying ongoing instances migrateable to the
                 new protocol. To support the protocol evolution
                 process, we have also developed database-backed GUI
                 tools on top of our existing system. The proposed
                 approach and tools can help service managers in
                 managing the evolution of ongoing instances when the
                 business protocols of services with which they are
                 interacting have changed.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "13",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "Business protocols; change impact analysis; decision
                 trees; dynamic evolution; ongoing instances; Web
                 services",
}

@Article{Schafer:2008:EFA,
  author =       "Michael Sch{\"a}fer and Peter Dolog and Wolfgang
                 Nejdl",
  title =        "An environment for flexible advanced compensations of
                 {Web} service transactions",
  journal =      j-TWEB,
  volume =       "2",
  number =       "2",
  pages =        "14:1--14:??",
  month =        apr,
  year =         "2008",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1346237.1346242",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:17:47 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Business to business integration has recently been
                 performed by employing Web service environments.
                 Moreover, such environments are being provided by major
                 players on the technology markets. Those environments
                 are based on open specifications for transaction
                 coordination. When a failure in such an environment
                 occurs, a compensation can be initiated to recover from
                 the failure. However, current environments have only
                 limited capabilities for compensations, and are usually
                 based on backward recovery. In this article, we
                 introduce an environment to deal with advanced
                 compensations based on forward recovery principles. We
                 extend the existing Web service transaction
                 coordination architecture and infrastructure in order
                 to support flexible compensation operations. We use a
                 contract-based approach, which allows the specification
                 of permitted compensations at runtime. We introduce
                 {\em abstract service\/} and {\em adapter\/}
                 components, which allow us to separate the compensation
                 logic from the coordination logic. In this way, we can
                 easily plug in or plug out different compensation
                 strategies based on a specification language defined on
                 top of basic compensation activities and complex
                 compensation types. Experiments with our approach and
                 environment show that such an approach to compensation
                 is feasible and beneficial. Additionally, we introduce
                 a cost-benefit model to evaluate the proposed
                 environment based on net value analysis. The evaluation
                 shows in which circumstances the environment is
                 economical.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "14",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "compensations; forward-recovery; transactions; Web
                 services",
}

@Article{Srivatsa:2008:MAL,
  author =       "Mudhakar Srivatsa and Arun Iyengar and Jian Yin and
                 Ling Liu",
  title =        "Mitigating application-level denial of service attacks
                 on {Web} servers: a client-transparent approach",
  journal =      j-TWEB,
  volume =       "2",
  number =       "3",
  pages =        "15:1--15:??",
  month =        jul,
  year =         "2008",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1377488.1377489",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:17:58 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Recently, we have seen increasing numbers of denial of
                 service (DoS) attacks against online services and Web
                 applications either for extortion reasons or for
                 impairing and even disabling the competition. These DoS
                 attacks have increasingly targeted the application
                 level. Application-level DoS attacks emulate the same
                 request syntax and network-level traffic
                 characteristics as those of legitimate clients, thereby
                 making the attacks much harder to detect and counter.
                 Moreover, such attacks often target bottleneck
                 resources such as disk bandwidth, database bandwidth,
                 and CPU resources. In this article, we propose handling
                 DoS attacks by using a twofold mechanism. First, we
                 perform admission control to limit the number of
                 concurrent clients served by the online service.
                 Admission control is based on port hiding that renders
                 the online service invisible to unauthorized clients by
                 hiding the port number on which the service accepts
                 incoming requests. Second, we perform congestion
                 control on admitted clients to allocate more resources
                 to good clients. Congestion control is achieved by
                 adaptively setting a client's priority level in
                 response to the client's requests in a way that can
                 incorporate application-level semantics. We present a
                 detailed evaluation of the proposed solution using two
                 sample applications: Apache HTTPD and the TPCW
                 benchmark (running on Apache Tomcat and IBM DB2). Our
                 experiments show that the proposed solution incurs low
                 performance overhead and is resilient to DoS attacks.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "15",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "client transparency; DoS Attacks; game theory; Web
                 servers",
}

@Article{White:2008:LPD,
  author =       "Ryen W. White and Mikhail Bilenko and Silviu
                 Cucerzan",
  title =        "Leveraging popular destinations to enhance {Web}
                 search interaction",
  journal =      j-TWEB,
  volume =       "2",
  number =       "3",
  pages =        "16:1--16:??",
  month =        jul,
  year =         "2008",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1377488.1377490",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:17:58 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "This article presents a novel Web search interaction
                 feature that for a given query provides links to Web
                 sites frequently visited by other users with similar
                 information needs. These popular destinations
                 complement traditional search results, allowing direct
                 navigation to authoritative resources for the query
                 topic. Destinations are identified using the history of
                 the search and browsing behavior of many users over an
                 extended time period, and their collective behavior
                 provides a basis for computing source authority. They
                 are drawn from the end of users' postquery browse
                 trails where users may cease searching once they find
                 relevant information. We describe a user study that
                 compared the suggestion of destinations with the
                 previously proposed suggestion of related queries as
                 well as with traditional, unaided Web search. Results
                 show that search enhanced by query suggestions
                 outperforms other systems in terms of subject
                 perceptions and search effectiveness for fact-finding
                 search tasks. However, search enhanced by destination
                 suggestions performs best for exploratory tasks with
                 its best performance obtained from mining past user
                 behavior at query-level granularity. We discuss the
                 implications of these and other findings from our study
                 for the design of search systems that utilize user
                 behavior, in particular, user browse trails and popular
                 destinations.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "16",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "enhanced Web search; search destinations; User
                 studies",
}

@Article{Andreolini:2008:MFS,
  author =       "Mauro Andreolini and Sara Casolari and Michele
                 Colajanni",
  title =        "Models and framework for supporting runtime decisions
                 in {Web-based} systems",
  journal =      j-TWEB,
  volume =       "2",
  number =       "3",
  pages =        "17:1--17:??",
  month =        jul,
  year =         "2008",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1377488.1377491",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:17:58 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Efficient management of distributed Web-based systems
                 requires several mechanisms that decide on request
                 dispatching, load balance, admission control, request
                 redirection. The algorithms behind these mechanisms
                 typically make fast decisions on the basis of the load
                 conditions of the system resources. The architecture
                 complexity and workloads characterizing most Web-based
                 services make it extremely difficult to deduce a
                 representative view of a resource load from collected
                 measures that show extreme variability even at
                 different time scales. Hence, any decision based on
                 instantaneous or average views of the system load may
                 lead to useless or even wrong actions. As an
                 alternative, we propose a two-phase strategy that first
                 aims to obtain a representative view of the load trend
                 from measured system values and then applies this
                 representation to support runtime decision systems. We
                 consider two classical problems behind decisions: how
                 to detect significant and nontransient load changes of
                 a system resource and how to predict its future load
                 behavior. The two-phase strategy is based on stochastic
                 functions that are characterized by a computational
                 complexity that is compatible with runtime decisions.
                 We describe, test, and tune the two-phase strategy by
                 considering as a first example a multitier Web-based
                 system that is subject to different classes of
                 realistic and synthetic workloads. Also, we integrate
                 the proposed strategy into a framework that we validate
                 by applying it to support runtime decisions in a
                 cluster Web system and in a locally distributed Network
                 Intrusion Detection System.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "17",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "distributed systems; load change detection; load
                 prediction; load representation; World Wide Web",
}

@Article{Amitay:2008:ISI,
  author =       "Einat Amitay and Andrei Broder",
  title =        "Introduction to special issue on query log analysis:
                 {Technology} and ethics",
  journal =      j-TWEB,
  volume =       "2",
  number =       "4",
  pages =        "18:1--18:??",
  month =        oct,
  year =         "2008",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1409220.1409221",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:18:06 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "18",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Cooper:2008:SQL,
  author =       "Alissa Cooper",
  title =        "A survey of query log privacy-enhancing techniques
                 from a policy perspective",
  journal =      j-TWEB,
  volume =       "2",
  number =       "4",
  pages =        "19:1--19:??",
  month =        oct,
  year =         "2008",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1409220.1409222",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:18:06 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "As popular search engines face the sometimes
                 conflicting interests of protecting privacy while
                 retaining query logs for a variety of uses, numerous
                 technical measures have been suggested to both enhance
                 privacy and preserve at least a portion of the utility
                 of query logs. This article seeks to assess seven of
                 these techniques against three sets of criteria: (1)
                 how well the technique protects privacy, (2) how well
                 the technique preserves the utility of the query logs,
                 and (3) how well the technique might be implemented as
                 a user control. A user control is defined as a
                 mechanism that allows individual Internet users to
                 choose to have the technique applied to their own query
                 logs.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "19",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "log; policy; Privacy; query; search",
}

@Article{Baeza-Yates:2008:DTO,
  author =       "Ricardo Baeza-Yates and Aristides Gionis and Flavio P.
                 Junqueira and Vanessa Murdock and Vassilis Plachouras
                 and Fabrizio Silvestri",
  title =        "Design trade-offs for search engine caching",
  journal =      j-TWEB,
  volume =       "2",
  number =       "4",
  pages =        "20:1--20:??",
  month =        oct,
  year =         "2008",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1409220.1409223",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:18:06 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "In this article we study the trade-offs in designing
                 efficient caching systems for Web search engines. We
                 explore the impact of different approaches, such as
                 static vs. dynamic caching, and caching query results
                 vs. caching posting lists. Using a query log spanning a
                 whole year, we explore the limitations of caching and
                 we demonstrate that caching posting lists can achieve
                 higher hit rates than caching query answers. We propose
                 a new algorithm for static caching of posting lists,
                 which outperforms previous methods. We also study the
                 problem of finding the optimal way to split the static
                 cache between answers and posting lists. Finally, we
                 measure how the changes in the query log influence the
                 effectiveness of static caching, given our observation
                 that the distribution of the queries changes slowly
                 over time. Our results and observations are applicable
                 to different levels of the data-access hierarchy, for
                 instance, for a memory/disk layer or a broker/remote
                 server layer.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "20",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "Caching; query logs; Web search",
}

@Article{Richardson:2008:LAW,
  author =       "Matthew Richardson",
  title =        "Learning about the world through long-term query
                 logs",
  journal =      j-TWEB,
  volume =       "2",
  number =       "4",
  pages =        "21:1--21:??",
  month =        oct,
  year =         "2008",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1409220.1409224",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:18:06 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "In this article, we demonstrate the value of long-term
                 query logs. Most work on query logs to date considers
                 only short-term (within-session) query information. In
                 contrast, we show that long-term query logs can be used
                 to learn about the world we live in. There are many
                 applications of this that lead not only to improving
                 the search engine for its users, but also potentially
                 to advances in other disciplines such as medicine,
                 sociology, economics, and more. In this article, we
                 will show how long-term query logs can be used for
                 these purposes, and that their potential is severely
                 reduced if the logs are limited to short time horizons.
                 We show that query effects are long-lasting, provide
                 valuable information, and might be used to
                 automatically make medical discoveries, build concept
                 hierarchies, and generally learn about the sociological
                 behavior of users. We believe these applications are
                 only the beginning of what can be done with the
                 information contained in long-term query logs, and see
                 this work as a step toward unlocking their potential.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "21",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "data mining; knowledge discovery; query logs; user
                 behavior",
}

@Article{Koutrika:2008:CST,
  author =       "Georgia Koutrika and Frans Adjie Effendi and
                 Zolt{\'{}}n Gy{\"o}ngyi and Paul Heymann and Hector
                 Garcia-Molina",
  title =        "Combating spam in tagging systems: an evaluation",
  journal =      j-TWEB,
  volume =       "2",
  number =       "4",
  pages =        "22:1--22:??",
  month =        oct,
  year =         "2008",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1409220.1409225",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:18:06 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Tagging systems allow users to interactively annotate
                 a pool of shared resources using descriptive strings
                 called {\em tags}. Tags are used to guide users to
                 interesting resources and help them build communities
                 that share their expertise and resources. As tagging
                 systems are gaining in popularity, they become more
                 susceptible to {\em tag spam\/}: misleading tags that
                 are generated in order to increase the visibility of
                 some resources or simply to confuse users. Our goal is
                 to understand this problem better. In particular, we
                 are interested in answers to questions such as: How
                 many malicious users can a tagging system tolerate
                 before results significantly degrade? What types of
                 tagging systems are more vulnerable to malicious
                 attacks? What would be the effort and the impact of
                 employing a trusted moderator to find bad postings? Can
                 a system automatically protect itself from spam, for
                 instance, by exploiting user tag patterns? In a quest
                 for answers to these questions, we introduce a
                 framework for modeling tagging systems and user tagging
                 behavior. We also describe a method for ranking
                 documents matching a tag based on taggers' reliability.
                 Using our framework, we study the behavior of existing
                 approaches under malicious attacks and the impact of a
                 moderator and our ranking method.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "22",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "bookmarking systems; tag spam; Tagging; tagging
                 models",
}

@Article{Rattenbury:2009:MEP,
  author =       "Tye Rattenbury and Mor Naaman",
  title =        "Methods for extracting place semantics from {Flickr}
                 tags",
  journal =      j-TWEB,
  volume =       "3",
  number =       "1",
  pages =        "1:1--1:??",
  month =        jan,
  year =         "2009",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1462148.1462149",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:18:15 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "We describe an approach for extracting semantics for
                 tags, unstructured text-labels assigned to resources on
                 the Web, based on each tag's usage patterns. In
                 particular, we focus on the problem of extracting place
                 semantics for tags that are assigned to photos on
                 Flickr, a popular-photo sharing Web site that supports
                 location (latitude/longitude) metadata for photos. We
                 propose the adaptation of two baseline methods,
                 inspired by well-known burst-analysis techniques, for
                 the task; we also describe two novel methods, TagMaps
                 and scale-structure identification. We evaluate the
                 methods on a subset of Flickr data. We show that our
                 scale-structure identification method outperforms
                 existing techniques and that a hybrid approach
                 generates further improvements (achieving 85\%
                 precision at 81\% recall). The approach and methods
                 described in this work can be used in other domains
                 such as geo-annotated Web pages, where text terms can
                 be extracted and associated with usage patterns.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "1",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "places; semantics; Tagging systems; tags",
}

@Article{Jackson:2009:PBD,
  author =       "Collin Jackson and Adam Barth and Andrew Bortz and
                 Weidong Shao and Dan Boneh",
  title =        "Protecting browsers from {DNS} rebinding attacks",
  journal =      j-TWEB,
  volume =       "3",
  number =       "1",
  pages =        "2:1--2:??",
  month =        jan,
  year =         "2009",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1462148.1462150",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:18:15 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "DNS rebinding attacks subvert the same-origin policy
                 of browsers, converting them into open network proxies.
                 Using DNS rebinding, an attacker can circumvent
                 organizational and personal firewalls, send spam email,
                 and defraud pay-per-click advertisers. We evaluate the
                 cost effectiveness of mounting DNS rebinding attacks,
                 finding that an attacker requires less than \$100 to
                 hijack 100,000 IP addresses. We analyze defenses to DNS
                 rebinding attacks, including improvements to the
                 classic ``DNS pinning,'' and recommend changes to
                 browser plug-ins, firewalls, and Web servers. Our
                 defenses have been adopted by plug-in vendors and by a
                 number of open-source firewall implementations.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "2",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "click fraud; DNS; firewall; Same-origin policy; spam",
}

@Article{Bar-Yossef:2009:DCD,
  author =       "Ziv Bar-Yossef and Idit Keidar and Uri Schonfeld",
  title =        "Do not crawl in the {DUST}: {Different URLs with
                 Similar Text}",
  journal =      j-TWEB,
  volume =       "3",
  number =       "1",
  pages =        "3:1--3:??",
  month =        jan,
  year =         "2009",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1462148.1462151",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:18:15 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "We consider the problem of DUST: Different URLs with
                 Similar Text. Such duplicate URLs are prevalent in Web
                 sites, as Web server software often uses aliases and
                 redirections, and dynamically generates the same page
                 from various different URL requests. We present a novel
                 algorithm, {\em DustBuster}, for uncovering DUST; that
                 is, for discovering rules that transform a given URL to
                 others that are likely to have similar content.
                 DustBuster mines DUST effectively from previous crawl
                 logs or Web server logs, {\em without\/} examining page
                 contents. Verifying these rules via sampling requires
                 fetching few actual Web pages. Search engines can
                 benefit from information about DUST to increase the
                 effectiveness of crawling, reduce indexing overhead,
                 and improve the quality of popularity statistics such
                 as PageRank.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "3",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "antialiasing; crawling; duplicate detection; Search
                 engines; URL normalization",
}

@Article{Xiao:2009:BSD,
  author =       "Xiangye Xiao and Qiong Luo and Dan Hong and Hongbo Fu
                 and Xing Xie and Wei-Ying Ma",
  title =        "Browsing on small displays by transforming {Web} pages
                 into hierarchically structured subpages",
  journal =      j-TWEB,
  volume =       "3",
  number =       "1",
  pages =        "4:1--4:??",
  month =        jan,
  year =         "2009",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1462148.1462152",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:18:15 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "We propose a new Web page transformation method to
                 facilitate Web browsing on handheld devices such as
                 Personal Digital Assistants (PDAs). In our approach, an
                 original Web page that does not fit on the screen is
                 transformed into a set of subpages, each of which fits
                 on the screen. This transformation is done through
                 slicing the original page into page blocks iteratively,
                 with several factors considered. These factors include
                 the size of the screen, the size of each page block,
                 the number of blocks in each transformed page, the
                 depth of the tree hierarchy that the transformed pages
                 form, as well as the semantic coherence between blocks.
                 We call the tree hierarchy of the transformed pages an
                 SP-tree. In an SP-tree, an internal node consists of a
                 textually enhanced thumbnail image with hyperlinks, and
                 a leaf node is a block extracted from a subpage of the
                 original Web page. We adaptively adjust the fanout and
                 the height of the SP-tree so that each thumbnail image
                 is clear enough for users to read, while at the same
                 time, the number of clicks needed to reach a leaf page
                 is few. Through this transformation algorithm, we
                 preserve the contextual information in the original Web
                 page and reduce scrolling. We have implemented this
                 transformation module on a proxy server and have
                 conducted usability studies on its performance. Our
                 system achieved a shorter task completion time compared
                 with that of transformations from the Opera browser in
                 nine of ten tasks. The average improvement on familiar
                 pages was 44\%. The average improvement on unfamiliar
                 pages was 37\%. Subjective responses were positive.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "4",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "Proxy; slicing tree; small displays; thumbnails; Web
                 browsing; Web page adaptation",
}

@Article{Gabrilovich:2009:CSQ,
  author =       "Evgeniy Gabrilovich and Andrei Broder and Marcus
                 Fontoura and Amruta Joshi and Vanja Josifovski and
                 Lance Riedel and Tong Zhang",
  title =        "Classifying search queries using the {Web} as a source
                 of knowledge",
  journal =      j-TWEB,
  volume =       "3",
  number =       "2",
  pages =        "5:1--5:??",
  month =        apr,
  year =         "2009",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1513876.1513877",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:18:23 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "We propose a methodology for building a robust query
                 classification system that can identify thousands of
                 query classes, while dealing in real time with the
                 query volume of a commercial Web search engine. We use
                 a pseudo relevance feedback technique: given a query,
                 we determine its topic by classifying the Web search
                 results retrieved by the query. Motivated by the needs
                 of search advertising, we primarily focus on rare
                 queries, which are the hardest from the point of view
                 of machine learning, yet in aggregate account for a
                 considerable fraction of search engine traffic.
                 Empirical evaluation confirms that our methodology
                 yields a considerably higher classification accuracy
                 than previously reported. We believe that the proposed
                 methodology will lead to better matching of online ads
                 to rare queries and overall to a better user
                 experience.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "5",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "Pseudo relevance feedback; query classification; Web
                 search",
}

@Article{Reay:2009:LSE,
  author =       "Ian Reay and Scott Dick and James Miller",
  title =        "A large-scale empirical study of {P3P} privacy
                 policies: {Stated} actions vs. legal obligations",
  journal =      j-TWEB,
  volume =       "3",
  number =       "2",
  pages =        "6:1--6:??",
  month =        apr,
  year =         "2009",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1513876.1513878",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:18:23 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Numerous studies over the past ten years have shown
                 that concern for personal privacy is a major impediment
                 to the growth of e-commerce. These concerns are so
                 serious that most if not all consumer watchdog groups
                 have called for some form of privacy protection for
                 Internet users. In response, many nations around the
                 world, including all European Union nations, Canada,
                 Japan, and Australia, have enacted national legislation
                 establishing mandatory safeguards for personal privacy.
                 However, recent evidence indicates that Web sites might
                 not be adhering to the requirements of this
                 legislation. The goal of this study is to examine the
                 posted privacy policies of Web sites, and compare these
                 statements to the legal mandates under which the Web
                 sites operate. We harvested all available P3P (Platform
                 for Privacy Preferences Protocol) documents from the
                 100,000 most popular Web sites (over 3,000 full
                 policies, and another 3,000 compact policies). This
                 allows us to undertake an automated analysis of
                 adherence to legal mandates on Web sites that most
                 impact the average Internet user. Our findings show
                 that Web sites generally do not even claim to follow
                 all the privacy-protection mandates in their legal
                 jurisdiction (we do not examine actual practice, only
                 posted policies). Furthermore, this general statement
                 appears to be true for every jurisdiction with privacy
                 laws and any significant number of P3P policies,
                 including European Union nations, Canada, Australia,
                 and Web sites in the USA Safe Harbor program.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "6",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "electronic commerce; legislation and enforcement; P3P;
                 Privacy protection",
}

@Article{Dourisboure:2009:ECD,
  author =       "Yon Dourisboure and Filippo Geraci and Marco
                 Pellegrini",
  title =        "Extraction and classification of dense implicit
                 communities in the {Web} graph",
  journal =      j-TWEB,
  volume =       "3",
  number =       "2",
  pages =        "7:1--7:??",
  month =        apr,
  year =         "2009",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1513876.1513879",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Fri Apr 24 18:18:23 MDT 2009",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The World Wide Web (WWW) is rapidly becoming important
                 for society as a medium for sharing data, information,
                 and services, and there is a growing interest in tools
                 for understanding collective behavior and emerging
                 phenomena in the WWW. In this article we focus on the
                 problem of searching and classifying {\em
                 communities\/} in the Web. Loosely speaking a community
                 is a group of pages related to a common interest. More
                 formally, communities have been associated in the
                 computer science literature with the existence of a
                 locally dense subgraph of the Web graph (where Web
                 pages are nodes and hyperlinks are arcs of the Web
                 graph). The core of our contribution is a new scalable
                 algorithm for finding relatively dense subgraphs in
                 massive graphs. We apply our algorithm on Web graphs
                 built on three publicly available large crawls of the
                 Web (with raw sizes up to 120M nodes and 1G arcs). The
                 effectiveness of our algorithm in finding dense
                 subgraphs is demonstrated experimentally by embedding
                 artificial communities in the Web graph and counting
                 how many of these are blindly found. Effectiveness
                 increases with the size and density of the communities:
                 it is close to 100\% for communities of thirty nodes or
                 more (even at low density). It is still about 80\% even
                 for communities of twenty nodes with density over 50\%
                 of the arcs present. At the lower extremes the
                 algorithm catches 35\% of dense communities made of ten
                 nodes. We also develop some sufficient conditions for
                 the detection of a community under some local graph
                 models and not-too-restrictive hypotheses. We complete
                 our {\em Community Watch\/} system by clustering the
                 communities found in the Web graph into homogeneous
                 groups by topic and labeling each group by
                 representative keywords.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "7",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "communities; detection of dense subgraph; Web graph",
}

@Article{Lee:2009:ISB,
  author =       "Hsin-Tsang Lee and Derek Leonard and Xiaoming Wang and
                 Dmitri Loguinov",
  title =        "{IRLbot}: {Scaling} to 6 billion pages and beyond",
  journal =      j-TWEB,
  volume =       "3",
  number =       "3",
  pages =        "8:1--8:??",
  month =        jun,
  year =         "2009",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1541822.1541823",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Tue Mar 16 09:28:38 MDT 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "This article shares our experience in designing a Web
                 crawler that can download billions of pages using a
                 single-server implementation and models its
                 performance. We first show that current crawling
                 algorithms cannot effectively cope with the sheer
                 volume of URLs generated in large crawls, highly
                 branching spam, legitimate multimillion-page blog
                 sites, and infinite loops created by server-side
                 scripts. We then offer a set of techniques for dealing
                 with these issues and test their performance in an
                 implementation we call IRLbot. In our recent experiment
                 that lasted 41 days, IRLbot running on a single server
                 successfully crawled 6.3 billion valid HTML pages (7.6
                 billion connection requests) and sustained an average
                 download rate of 319 mb/s (1,789 pages/s). Unlike our
                 prior experiments with algorithms proposed in related
                 work, this version of IRLbot did not experience any
                 bottlenecks and successfully handled content from over
                 117 million hosts, parsed out 394 billion links, and
                 discovered a subset of the Web graph with 41 billion
                 unique nodes.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "8",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "crawling; IRLbot; large scale",
}

@Article{Tappenden:2009:CDS,
  author =       "Andrew F. Tappenden and James Miller",
  title =        "Cookies: a deployment study and the testing
                 implications",
  journal =      j-TWEB,
  volume =       "3",
  number =       "3",
  pages =        "9:1--9:??",
  month =        jun,
  year =         "2009",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1541822.1541824",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Tue Mar 16 09:28:38 MDT 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The results of an extensive investigation of cookie
                 deployment amongst 100,000 Internet sites are
                 presented. Cookie deployment is found to be approaching
                 universal levels and hence there exists an associated
                 need for relevant Web and software engineering
                 processes, specifically testing strategies which
                 actively consider cookies. The semi-automated
                 investigation demonstrates that over two-thirds of the
                 sites studied deploy cookies. The investigation
                 specifically examines the use of first-party,
                 third-party, sessional, and persistent cookies within
                 Web-based applications, identifying the presence of a
                 P3P policy and dynamic Web technologies as major
                 predictors of cookie usage. The results are juxtaposed
                 with the lack of testing strategies present in the
                 literature. A number of real-world examples, including
                 two case studies are presented, further accentuating
                 the need for comprehensive testing strategies for
                 Web-based applications. The use of antirandom test case
                 generation is explored with respect to the testing
                 issues discussed. Finally, a number of seeding vectors
                 are presented, providing a basis for testing cookies
                 within Web-based applications.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "9",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "Cookies; Internet browser; software testing; Web
                 engineering; Web technologies",
}

@Article{Comuzzi:2009:FQB,
  author =       "Marco Comuzzi and Barbara Pernici",
  title =        "A framework for {QoS}-based {Web} service
                 contracting",
  journal =      j-TWEB,
  volume =       "3",
  number =       "3",
  pages =        "10:1--10:??",
  month =        jun,
  year =         "2009",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1541822.1541825",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Tue Mar 16 09:28:38 MDT 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The extensive adoption of Web service-based
                 applications in dynamic business scenarios, such as
                 on-demand computing or highly reconfigurable virtual
                 enterprises, advocates for methods and tools for the
                 management of Web service nonfunctional aspects, such
                 as Quality of Service (QoS). Concerning contracts on
                 Web service QoS, the literature has mostly focused on
                 the contract definition and on mechanisms for contract
                 enactment, such as the monitoring of the satisfaction
                 of negotiated QoS guarantees. In this context, this
                 article proposes a framework for the automation of the
                 Web service contract specification and establishment.
                 An extensible model for defining both domain-dependent
                 and domain-independent Web service QoS dimensions and a
                 method for the automation of the contract establishment
                 phase are proposed. We describe a matchmaking algorithm
                 for the ranking of functionally equivalent services,
                 which orders services on the basis of their ability to
                 fulfill the service requestor requirements, while
                 maintaining the price below a specified budget. We also
                 provide an algorithm for the configuration of the
                 negotiable part of the QoS Service-Level Agreement
                 (SLA), which is used to configure the agreement with
                 the top-ranked service identified in the matchmaking
                 phase. Experimental results show that, in a utility
                 theory perspective, the contract establishment phase
                 leads to efficient outcomes. We envision two advanced
                 application scenarios for the Web service contracting
                 framework proposed in this article. First, it can be
                 used to enhance Web services self-healing properties in
                 reaction to QoS-related service failures; second, it
                 can be exploited in process optimization for the online
                 reconfiguration of candidate Web services QoS SLAs.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "10",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "matchmaking; negotiation; QoS; service selection; SLA;
                 Web service",
}

@Article{Pilioura:2009:UPD,
  author =       "Thomi Pilioura and Aphrodite Tsalgatidou",
  title =        "Unified publication and discovery of semantic {Web}
                 services",
  journal =      j-TWEB,
  volume =       "3",
  number =       "3",
  pages =        "11:1--11:??",
  month =        jun,
  year =         "2009",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1541822.1541826",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Tue Mar 16 09:28:38 MDT 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The challenge of publishing and discovering Web
                 services has recently received lots of attention.
                 Various solutions to this problem have been proposed
                 which, apart from their offered advantages, suffer the
                 following disadvantages: (i) most of them are
                 syntactic-based, leading to poor precision and recall,
                 (ii) they are not scalable to large numbers of
                 services, and (iii) they are incompatible, thus
                 yielding in cumbersome service publication and
                 discovery. This article presents the principles, the
                 functionality, and the design of PYRAMID-S which
                 addresses these disadvantages by providing a scalable
                 framework for unified publication and discovery of
                 semantically enhanced services over heterogeneous
                 registries. PYRAMID-S uses a hybrid peer-to-peer
                 topology to organize Web service registries based on
                 domains. In such a topology, each Registry retains its
                 autonomy, meaning that it can use the publication and
                 discovery mechanisms as well as the ontology of its
                 choice. The viability of this approach is demonstrated
                 through the implementation and experimental analysis of
                 a prototype.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "11",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "evaluation; PYRAMID-S; scalable; semantic Web
                 services; unified; Web service discovery; Web service
                 publication",
}

@Article{Golbeck:2009:TNP,
  author =       "Jennifer Golbeck",
  title =        "Trust and nuanced profile similarity in online social
                 networks",
  journal =      j-TWEB,
  volume =       "3",
  number =       "4",
  pages =        "12:1--12:??",
  month =        sep,
  year =         "2009",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1594173.1594174",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Tue Mar 16 09:28:43 MDT 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "12",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Singh:2009:SSO,
  author =       "Aameek Singh and Mudhakar Srivatsa and Ling Liu",
  title =        "Search-as-a-service: {Outsourced} search over
                 outsourced storage",
  journal =      j-TWEB,
  volume =       "3",
  number =       "4",
  pages =        "13:1--13:??",
  month =        sep,
  year =         "2009",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1594173.1594175",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Tue Mar 16 09:28:43 MDT 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "13",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Robu:2009:ECS,
  author =       "Valentin Robu and Harry Halpin and Hana Shepherd",
  title =        "Emergence of consensus and shared vocabularies in
                 collaborative tagging systems",
  journal =      j-TWEB,
  volume =       "3",
  number =       "4",
  pages =        "14:1--14:??",
  month =        sep,
  year =         "2009",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1594173.1594176",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Tue Mar 16 09:28:43 MDT 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "14",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Zheng:2010:UTM,
  author =       "Yu Zheng and Yukun Chen and Quannan Li and Xing Xie
                 and Wei-Ying Ma",
  title =        "Understanding transportation modes based on {GPS} data
                 for {Web} applications",
  journal =      j-TWEB,
  volume =       "4",
  number =       "1",
  pages =        "1:1--1:??",
  month =        jan,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1658373.1658374",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Tue Mar 16 09:28:45 MDT 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "1",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Li:2010:DSO,
  author =       "Guoli Li and Vinod Muthusamy and Hans-Arno Jacobsen",
  title =        "A distributed service-oriented architecture for
                 business process execution",
  journal =      j-TWEB,
  volume =       "4",
  number =       "1",
  pages =        "2:1--2:??",
  month =        jan,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1658373.1658375",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Tue Mar 16 09:28:45 MDT 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "2",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Montali:2010:DSV,
  author =       "Marco Montali and Maja Pesic and Wil M. P. van der
                 Aalst and Federico Chesani and Paola Mello and Sergio
                 Storari",
  title =        "Declarative specification and verification of service
                 choreographies",
  journal =      j-TWEB,
  volume =       "4",
  number =       "1",
  pages =        "3:1--3:??",
  month =        jan,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1658373.1658376",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Tue Mar 16 09:28:45 MDT 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "3",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Almishari:2010:APD,
  author =       "Mishari Almishari and Xiaowei Yang",
  title =        "Ads-portal domains: {Identification} and
                 measurements",
  journal =      j-TWEB,
  volume =       "4",
  number =       "2",
  pages =        "4:1--4:??",
  month =        apr,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1734200.1734201",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Sat Aug 14 15:42:32 MDT 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "An ads-portal domain refers to a Web domain that shows
                 only advertisements, served by a third-party
                 advertisement syndication service, in the form of ads
                 listing. We develop a machine-learning-based classifier
                 to identify ads-portal domains, which has 96\%
                 accuracy. We use this classifier to measure the
                 prevalence of ads-portal domains on the Internet.
                 Surprisingly, 28.3/25\% of the (two-level) {\tt *.com}
                 /{\tt *.net} web domains are ads-portal domains. Also,
                 41/39.8\% of {\tt *.com} /{\tt *.net} ads-portal
                 domains are typos of well-known domains, also known as
                 typo-squatting domains. In addition, we use the
                 classifier along with DNS trace files to estimate how
                 often Internet users visit ads-portal domains. It turns
                 out that $ \approx 5 \% $ of the two-level {\tt *.com},
                 {\tt *.net}, {\tt *.org}, {\tt *.biz} and {\tt *.info}
                 web domains on the traces are ads-portal domains and $
                 \approx 50 \% $ of these accessed ads-portal domains
                 are typos. These numbers show that ads-portal domains
                 and typo-squatting ads-portal domains are prevalent on
                 the Internet and successful in attracting many visits.
                 Our classifier represents a step towards better
                 categorizing the web documents. It can also be helpful
                 to search engines ranking algorithms, helpful in
                 identifying web spams that redirects to ads-portal
                 domains, and used to discourage access to
                 typo-squatting ads-portal domains.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "4",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "Ads-portal; advertisement syndication; data mining;
                 parked domain; parking service; Web characterization",
}

@Article{Jurca:2010:RIB,
  author =       "Radu Jurca and Florent Garcin and Arjun Talwar and Boi
                 Faltings",
  title =        "Reporting incentives and biases in online review
                 forums",
  journal =      j-TWEB,
  volume =       "4",
  number =       "2",
  pages =        "5:1--5:??",
  month =        apr,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1734200.1734202",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Sat Aug 14 15:42:32 MDT 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Online reviews have become increasingly popular as a
                 way to judge the quality of various products and
                 services. However, recent work demonstrates that the
                 absence of reporting incentives leads to a biased set
                 of reviews that may not reflect the true quality. In
                 this paper, we investigate underlying factors that
                 influence users when reporting feedback. In particular,
                 we study both reporting incentives and reporting biases
                 observed in a widely used review forum, the Tripadvisor
                 Web site. We consider three sources of information:
                 first, the numerical ratings left by the user for
                 different aspects of quality; second, the textual
                 comment accompanying a review; third, the patterns in
                 the time sequence of reports. We first show that groups
                 of users who discuss a certain feature at length are
                 more likely to agree in their ratings. Second, we show
                 that users are more motivated to give feedback when
                 they perceive a greater risk involved in a transaction.
                 Third, a user's rating partly reflects the difference
                 between true quality and prior expectation of quality,
                 as inferred from previous reviews. We finally observe
                 that because of these biases, when averaging review
                 scores there are strong differences between the mean
                 and the median. We speculate that the median may be a
                 better way to summarize the ratings.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "5",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "Online reviews; reputation mechanisms",
}

@Article{Vlachos:2010:ODB,
  author =       "Michail Vlachos and Suleyman S. Kozat and Philip S.
                 Yu",
  title =        "Optimal distance bounds for fast search on compressed
                 time-series query logs",
  journal =      j-TWEB,
  volume =       "4",
  number =       "2",
  pages =        "6:1--6:??",
  month =        apr,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1734200.1734203",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Sat Aug 14 15:42:32 MDT 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Consider a database of time-series, where each
                 datapoint in the series records the total number of
                 users who asked for a specific query at an Internet
                 search engine. Storage and analysis of such logs can be
                 very beneficial for a search company from multiple
                 perspectives. First, from a data organization
                 perspective, because query Weblogs capture important
                 trends and statistics, they can help enhance and
                 optimize the search experience (keyword recommendation,
                 discovery of news events). Second, Weblog data can
                 provide an important polling mechanism for the
                 microeconomic aspects of a search engine, since they
                 can facilitate and promote the advertising facet of the
                 search engine (understand what users request and when
                 they request it).\par

                 Due to the sheer amount of time-series Weblogs,
                 manipulation of the logs in a compressed form is an
                 impeding necessity for fast data processing and compact
                 storage requirements. Here, we explicate how to compute
                 the lower and upper distance bounds on the time-series
                 logs when working directly on their compressed form.
                 Optimal distance estimation means tighter bounds,
                 leading to better candidate selection/elimination and
                 ultimately faster search performance. Our derivation of
                 the optimal distance bounds is based on the careful
                 analysis of the problem using optimization principles.
                 The experimental evaluation suggests a clear
                 performance advantage of the proposed method, compared
                 to previous compression/search techniques. The
                 presented method results in a 10--30\% improvement on
                 distance estimations, which in turn leads to 25--80\%
                 improvement on the search performance.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "6",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Fraternali:2010:ERI,
  author =       "Piero Fraternali and Sara Comai and Alessandro Bozzon
                 and Giovanni Toffetti Carughi",
  title =        "Engineering rich {Internet} applications with a
                 model-driven approach",
  journal =      j-TWEB,
  volume =       "4",
  number =       "2",
  pages =        "7:1--7:??",
  month =        apr,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1734200.1734204",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Sat Aug 14 15:42:32 MDT 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Rich Internet Applications (RIAs) have introduced
                 powerful novel functionalities into the Web
                 architecture, borrowed from client-server and desktop
                 applications. The resulting platforms allow designers
                 to improve the user's experience, by exploiting
                 client-side data and computation, bidirectional
                 client-server communication, synchronous and
                 asynchronous events, and rich interface widgets.
                 However, the rapid evolution of RIA technologies
                 challenges the Model-Driven Development methodologies
                 that have been successfully applied in the past decade
                 to traditional Web solutions. This paper illustrates an
                 evolutionary approach for incorporating a wealth of RIA
                 features into an existing Web engineering methodology
                 and notation. The experience demonstrates that it is
                 possible to model RIA application requirements at a
                 high-level using a platform-independent notation, and
                 generate the client-side and server-side code
                 automatically. The resulting approach is evaluated in
                 terms of expressive power, ease of use, and
                 implementability.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "7",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "information interfaces and presentation; information
                 storage and retrieval; model-driven development; Rich
                 Internet applications; Web engineering",
}

@Article{Xiao:2010:LSS,
  author =       "Xiangye Xiao and Qiong Luo and Zhisheng Li and Xing
                 Xie and Wei-Ying Ma",
  title =        "A large-scale study on map search logs",
  journal =      j-TWEB,
  volume =       "4",
  number =       "3",
  pages =        "8:1--8:??",
  month =        jul,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1806916.1806917",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Sat Aug 14 15:42:40 MDT 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Map search engines, such as Google Maps, Yahoo! Maps,
                 and Microsoft Live Maps, allow users to explicitly
                 specify a target geographic location, either in
                 keywords or on the map, and to search businesses,
                 people, and other information of that location. In this
                 article, we report a first study on a million-entry map
                 search log. We identify three key attributes of a map
                 search record --- the keyword query, the target
                 location and the user location, and examine the
                 characteristics of these three dimensions separately as
                 well as the associations between them. Comparing our
                 results with those previously reported on logs of
                 general search engines and mobile search engines,
                 including those for geographic queries, we discover the
                 following unique features of map search: (1) People use
                 longer queries and modify queries more frequently in a
                 session than in general search and mobile search;
                 People view fewer result pages per query than in
                 general search; (2) The popular query topics in map
                 search are different from those in general search and
                 mobile search; (3) The target locations in a session
                 change within 50 kilometers for almost 80\% of the
                 sessions; (4) Queries, search target locations and user
                 locations (both at the city level) all follow the power
                 law distribution; (5) One third of queries are issued
                 for target locations within 50 kilometers from the user
                 locations; (6) The distribution of a query over target
                 locations appears to follow the geographic location of
                 the queried entity.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "8",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "local search; log analysis; Map search; query
                 categorization; search interface; user behavior",
}

@Article{Malak:2010:MWQ,
  author =       "Ghazwa Malak and Houari Sahraoui and Linda Badri and
                 Mourad Badri",
  title =        "Modeling {Web} quality using a probabilistic approach:
                 an empirical validation",
  journal =      j-TWEB,
  volume =       "4",
  number =       "3",
  pages =        "9:1--9:??",
  month =        jul,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1806916.1806918",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Sat Aug 14 15:42:40 MDT 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Web-based applications are software systems that
                 continuously evolve to meet users' needs and to adapt
                 to new technologies. Assuring their quality is then a
                 difficult, but essential task. In fact, a large number
                 of factors can affect their quality. Considering these
                 factors and their interaction involves managing
                 uncertainty and subjectivity inherent to this kind of
                 applications. In this article, we present a
                 probabilistic approach for building Web quality models
                 and the associated assessment method. The proposed
                 approach is based on Bayesian Networks. A model is
                 built following a four-step process consisting in
                 collecting quality characteristics, refining them,
                 building a model structure, and deriving the model
                 parameters.\par

                 The feasibility of the approach is illustrated on the
                 important quality characteristic of {\em Navigability
                 design}. To validate the produced model, we conducted
                 an experimental study with 20 subjects and 40 web
                 pages. The results obtained show that the scores given
                 by the used model are strongly correlated with
                 navigability as perceived and experienced by the
                 users.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "9",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "Bayesian networks; Navigability design; probabilistic
                 approach; quality evaluation; Web applications",
}

@Article{Poblete:2010:PPQ,
  author =       "Barbara Poblete and Myra Spiliopoulou and Ricardo
                 Baeza-Yates",
  title =        "Privacy-preserving query log mining for business
                 confidentiality protection",
  journal =      j-TWEB,
  volume =       "4",
  number =       "3",
  pages =        "10:1--10:??",
  month =        jul,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1806916.1806919",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Sat Aug 14 15:42:40 MDT 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "We introduce the concern of confidentiality protection
                 of business information for the publication of search
                 engine query logs and derived data. We study business
                 confidentiality, as the protection of nonpublic data
                 from institutions, such as companies and people in the
                 public eye. In particular, we relate this concern to
                 the involuntary exposure of confidential Web site
                 information, and we transfer this problem into the
                 field of privacy-preserving data mining. We
                 characterize the possible adversaries interested in
                 disclosing Web site confidential data and the attack
                 strategies that they could use. These attacks are based
                 on different vulnerabilities found in query log for
                 which we present several anonymization heuristics to
                 prevent them. We perform an experimental evaluation to
                 estimate the remaining utility of the log after the
                 application of our anonymization techniques. Our
                 experimental results show that a query log can be
                 anonymized against these specific attacks while
                 retaining a significant volume of useful data.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "10",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "Privacy preservation; queries; query log publication;
                 Web sites",
}

@Article{Consens:2010:EXW,
  author =       "Mariano P. Consens and Ren{\'e}e J. Miller and Flavio
                 Rizzolo and Alejandro A. Vaisman",
  title =        "Exploring {XML} {Web} collections with {DescribeX}",
  journal =      j-TWEB,
  volume =       "4",
  number =       "3",
  pages =        "11:1--11:??",
  month =        jul,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1806916.1806920",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Sat Aug 14 15:42:40 MDT 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "As Web applications mature and evolve, the nature of
                 the semistructured data that drives these applications
                 also changes. An important trend is the need for
                 increased flexibility in the structure of Web
                 documents. Hence, applications cannot rely solely on
                 schemas to provide the complex knowledge needed to
                 visualize, use, query and manage documents. Even when
                 XML Web documents are valid with regard to a schema,
                 the actual structure of such documents may exhibit
                 significant variations across collections for several
                 reasons: the schema may be very lax (e.g., RSS feeds),
                 the schema may be large and different subsets of it may
                 be used in different documents (e.g., industry
                 standards like UBL), or open content models may allow
                 arbitrary schemas to be mixed (e.g., RSS extensions
                 like those used for podcasting). For these reasons,
                 many applications that incorporate XPath queries to
                 process a large Web document collection require an
                 understanding of the actual structure present in the
                 collection, and not just the schema.\par

                 To support modern Web applications, we introduce
                 DescribeX, a powerful framework that is capable of
                 describing complex XML summaries of Web collections.
                 DescribeX supports the construction of heterogeneous
                 summaries that can be declaratively defined and refined
                 by means of axis path regular expression (AxPREs).
                 AxPREs provide the flexibility necessary for
                 declaratively defining complex mappings between
                 instance nodes (in the documents) and summary nodes.
                 These mappings are capable of expressing order and
                 cardinality, among other properties, which can
                 significantly help in the understanding of the
                 structure of large collections of XML documents and
                 enhance the performance of Web applications over these
                 collections. DescribeX captures most summary proposals
                 in the literature by providing (for the first time) a
                 common declarative definition for them. Experimental
                 results demonstrate the scalability of DescribeX
                 summary operations (summary creation, as well as
                 refinement and stabilization, two key enablers for
                 tailoring summaries) on multi-gigabyte Web
                 collections.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "11",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "Semistructured data; structural summaries; XML;
                 XPath",
}

@Article{Adams:2010:DLS,
  author =       "Brett Adams and Dinh Phung and Svetha Venkatesh",
  title =        "Discovery of latent subcommunities in a blog's
                 readership",
  journal =      j-TWEB,
  volume =       "4",
  number =       "3",
  pages =        "12:1--12:??",
  month =        jul,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1806916.1806921",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Sat Aug 14 15:42:40 MDT 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The blogosphere has grown to be a mainstream forum of
                 social interaction as well as a commercially attractive
                 source of information and influence. Tools are needed
                 to better understand how communities that adhere to
                 individual blogs are constituted in order to facilitate
                 new personal, socially-focused browsing paradigms, and
                 understand how blog content is consumed, which is of
                 interest to blog authors, big media, and search. We
                 present a novel approach to blog subcommunity
                 characterization by modeling individual blog readers
                 using mixtures of an extension to the LDA family that
                 jointly models phrases and time, Ngram Topic over Time
                 (NTOT), and cluster with a number of similarity
                 measures using Affinity Propagation. We experiment with
                 two datasets: a small set of blogs whose authors
                 provide feedback, and a set of popular, highly
                 commented blogs, which provide indicators of algorithm
                 scalability and interpretability without prior
                 knowledge of a given blog. The results offer useful
                 insight to the blog authors about their commenting
                 community, and are observed to offer an integrated
                 perspective on the topics of discussion and members
                 engaged in those discussions for unfamiliar blogs. Our
                 approach also holds promise as a component of solutions
                 to related problems, such as online entity resolution
                 and role discovery.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "12",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "affinity propagation; Blog; topic models; Web
                 communities",
}

@Article{Kiciman:2010:APR,
  author =       "Emre Kiciman and Benjamin Livshits",
  title =        "{AjaxScope}: a Platform for Remotely Monitoring the
                 Client-Side Behavior of {Web 2.0} Applications",
  journal =      j-TWEB,
  volume =       "4",
  number =       "4",
  pages =        "13:1--13:??",
  month =        sep,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1841909.1841910",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Tue Nov 23 12:48:27 MST 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "13",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Bex:2010:LDR,
  author =       "Geert Jan Bex and Wouter Gelade and Frank Neven and
                 Stijn Vansummeren",
  title =        "Learning Deterministic Regular Expressions for the
                 Inference of Schemas from {XML} Data",
  journal =      j-TWEB,
  volume =       "4",
  number =       "4",
  pages =        "14:1--14:??",
  month =        sep,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1841909.1841911",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Tue Nov 23 12:48:27 MST 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "14",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Bailey:2010:MHQ,
  author =       "Peter Bailey and Ryen W. White and Han Liu and
                 Giridhar Kumaran",
  title =        "Mining Historic Query Trails to Label Long and Rare
                 Search Engine Queries",
  journal =      j-TWEB,
  volume =       "4",
  number =       "4",
  pages =        "15:1--15:??",
  month =        sep,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1841909.1841912",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Tue Nov 23 12:48:27 MST 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "15",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Claude:2010:FCW,
  author =       "Francisco Claude and Gonzalo Navarro",
  title =        "Fast and Compact {Web} Graph Representations",
  journal =      j-TWEB,
  volume =       "4",
  number =       "4",
  pages =        "16:1--16:??",
  month =        sep,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1841909.1841913",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Tue Nov 23 12:48:27 MST 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "16",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Swaminathan:2010:RRM,
  author =       "Ashwin Swaminathan and Renan G. Cattelan and Ydo
                 Wexler and Cherian V. Mathew and Darko Kirovski",
  title =        "Relating Reputation and Money in Online Markets",
  journal =      j-TWEB,
  volume =       "4",
  number =       "4",
  pages =        "17:1--17:??",
  month =        sep,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1841909.1841914",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Tue Nov 23 12:48:27 MST 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "17",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Riedl:2011:ISI,
  author =       "John Riedl and Barry Smyth",
  title =        "Introduction to special issue on recommender systems",
  journal =      j-TWEB,
  volume =       "5",
  number =       "1",
  pages =        "1:1--1:??",
  month =        feb,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1921591.1921592",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Mon Mar 28 11:56:06 MDT 2011",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "1",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Cacheda:2011:CCF,
  author =       "Fidel Cacheda and V{\'\i}ctor Carneiro and Diego
                 Fern{\'a}ndez and Vreixo Formoso",
  title =        "Comparison of collaborative filtering algorithms:
                 Limitations of current techniques and proposals for
                 scalable, high-performance recommender systems",
  journal =      j-TWEB,
  volume =       "5",
  number =       "1",
  pages =        "2:1--2:??",
  month =        feb,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1921591.1921593",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Mon Mar 28 11:56:06 MDT 2011",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "2",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Umyarov:2011:UEA,
  author =       "Akhmed Umyarov and Alexander Tuzhilin",
  title =        "Using external aggregate ratings for improving
                 individual recommendations",
  journal =      j-TWEB,
  volume =       "5",
  number =       "1",
  pages =        "3:1--3:??",
  month =        feb,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1921591.1921594",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Mon Mar 28 11:56:06 MDT 2011",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "3",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Song:2011:ATR,
  author =       "Yang Song and Lu Zhang and C. Lee Giles",
  title =        "Automatic tag recommendation algorithms for social
                 recommender systems",
  journal =      j-TWEB,
  volume =       "5",
  number =       "1",
  pages =        "4:1--4:??",
  month =        feb,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1921591.1921595",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Mon Mar 28 11:56:06 MDT 2011",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "4",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Zheng:2011:RFL,
  author =       "Yu Zheng and Lizhu Zhang and Zhengxin Ma and Xing Xie
                 and Wei-Ying Ma",
  title =        "Recommending friends and locations based on individual
                 location history",
  journal =      j-TWEB,
  volume =       "5",
  number =       "1",
  pages =        "5:1--5:??",
  month =        feb,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1921591.1921596",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Mon Mar 28 11:56:06 MDT 2011",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "5",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Wu:2011:TDQ,
  author =       "Mingfang Wu and Falk Scholer and Andrew Turpin",
  title =        "Topic Distillation with Query-Dependent Link
                 Connections and Page Characteristics",
  journal =      j-TWEB,
  volume =       "5",
  number =       "2",
  pages =        "6:1--6:??",
  month =        may,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1961659.1961660",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Tue Jun 7 18:44:15 MDT 2011",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "6",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Hurley:2011:HBP,
  author =       "John Hurley and Emi Garcia-Palacios and Sakir Sezer",
  title =        "Host-Based {P2P} Flow Identification and Use in
                 Real-Time",
  journal =      j-TWEB,
  volume =       "5",
  number =       "2",
  pages =        "7:1--7:??",
  month =        may,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1961659.1961661",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Tue Jun 7 18:44:15 MDT 2011",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "7",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Mitra:2011:CWB,
  author =       "Siddharth Mitra and Mayank Agrawal and Amit Yadav and
                 Niklas Carlsson and Derek Eager and Anirban Mahanti",
  title =        "Characterizing {Web}-Based Video Sharing Workloads",
  journal =      j-TWEB,
  volume =       "5",
  number =       "2",
  pages =        "8:1--8:??",
  month =        may,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1961659.1961662",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Tue Jun 7 18:44:15 MDT 2011",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "8",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Ozcan:2011:CAS,
  author =       "Rifat Ozcan and Ismail Sengor Altingovde and
                 {\"O}zg{\"u}r Ulusoy",
  title =        "Cost-Aware Strategies for Query Result Caching in
                 {Web} Search Engines",
  journal =      j-TWEB,
  volume =       "5",
  number =       "2",
  pages =        "9:1--9:??",
  month =        may,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1961659.1961663",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Tue Jun 7 18:44:15 MDT 2011",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "9",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Valderas:2011:SRS,
  author =       "Pedro Valderas and Vicente Pelechano",
  title =        "A Survey of Requirements Specification in Model-Driven
                 Development of {Web} Applications",
  journal =      j-TWEB,
  volume =       "5",
  number =       "2",
  pages =        "10:1--10:??",
  month =        may,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1961659.1961664",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Tue Jun 7 18:44:15 MDT 2011",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "10",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Grier:2011:DIO,
  author =       "Chris Grier and Shuo Tang and Samuel T. King",
  title =        "Designing and Implementing the {OP} and {OP2} {Web}
                 Browsers",
  journal =      j-TWEB,
  volume =       "5",
  number =       "2",
  pages =        "11:1--11:??",
  month =        may,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1961659.1961665",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Tue Jun 7 18:44:15 MDT 2011",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "11",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Koutsonikola:2011:CDL,
  author =       "Vassiliki Koutsonikola and Athena Vakali",
  title =        "A Clustering-Driven {LDAP} Framework",
  journal =      j-TWEB,
  volume =       "5",
  number =       "3",
  pages =        "12:1--12:??",
  month =        jul,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1993053.1993054",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Thu Aug 18 13:57:29 MDT 2011",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "12",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Paci:2011:AAC,
  author =       "Federica Paci and Massimo Mecella and Mourad Ouzzani
                 and Elisa Bertino",
  title =        "{ACConv} -- An Access Control Model for Conversational
                 {Web} Services",
  journal =      j-TWEB,
  volume =       "5",
  number =       "3",
  pages =        "13:1--13:??",
  month =        jul,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1993053.1993055",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Thu Aug 18 13:57:29 MDT 2011",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "13",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Zeginis:2011:CDR,
  author =       "Dimitris Zeginis and Yannis Tzitzikas and Vassilis
                 Christophides",
  title =        "On Computing Deltas of {RDF/S} Knowledge Bases",
  journal =      j-TWEB,
  volume =       "5",
  number =       "3",
  pages =        "14:1--14:??",
  month =        jul,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1993053.1993056",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Thu Aug 18 13:57:29 MDT 2011",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "14",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Baykan:2011:CSF,
  author =       "Eda Baykan and Monika Henzinger and Ludmila Marian and
                 Ingmar Weber",
  title =        "A Comprehensive Study of Features and Algorithms for
                 {URL}-Based Topic Classification",
  journal =      j-TWEB,
  volume =       "5",
  number =       "3",
  pages =        "15:1--15:??",
  month =        jul,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1993053.1993057",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Thu Aug 18 13:57:29 MDT 2011",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "15",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Tuchinda:2011:BMD,
  author =       "Rattapoom Tuchinda and Craig A. Knoblock and Pedro
                 Szekely",
  title =        "Building Mashups by Demonstration",
  journal =      j-TWEB,
  volume =       "5",
  number =       "3",
  pages =        "16:1--16:??",
  month =        jul,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1993053.1993058",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  bibdate =      "Thu Aug 18 13:57:29 MDT 2011",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "16",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Alzoubi:2011:PAA,
  author =       "Hussein A. Alzoubi and Seungjoon Lee and Michael
                 Rabinovich and Oliver Spatscheck and Jacobus {Van Der
                 Merwe}",
  title =        "A Practical Architecture for an {Anycast CDN}",
  journal =      j-TWEB,
  volume =       "5",
  number =       "4",
  pages =        "17:1--17:??",
  month =        oct,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2019643.2019644",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Mar 16 12:37:40 MDT 2012",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "IP Anycast has many attractive features for any
                 service that involve the replication of multiple
                 instances across the Internet. IP Anycast allows
                 multiple instances of the same service to be
                 `naturally' discovered, and requests for this service
                 to be delivered to the closest instance. However, while
                 briefly considered as an enabler for content delivery
                 networks (CDNs) when they first emerged, IP Anycast was
                 deemed infeasible in that environment. The main reasons
                 for this decision were the lack of load awareness of IP
                 Anycast and unwanted side effects of Internet routing
                 changes on the IP Anycast mechanism. In this article we
                 re-evaluate IP Anycast for CDNs by proposing a
                 load-aware IP Anycast CDN architecture. Our
                 architecture is prompted by recent developments in
                 route control technology, as well as better
                 understanding of the behavior of IP Anycast in
                 operational settings. Our architecture makes use of
                 route control mechanisms to take server and network
                 load into account to realize load-aware Anycast. We
                 show that the resulting redirection requirements can be
                 formulated as a Generalized Assignment Problem and
                 present practical algorithms that address these
                 requirements while at the same time limiting connection
                 disruptions that plague regular IP Anycast. We evaluate
                 our algorithms through trace based simulation using
                 traces obtained from a production CDN network.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "17",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Bar-Yossef:2011:ESE,
  author =       "Ziv Bar-Yossef and Maxim Gurevich",
  title =        "Efficient Search Engine Measurements",
  journal =      j-TWEB,
  volume =       "5",
  number =       "4",
  pages =        "18:1--18:??",
  month =        oct,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2019643.2019645",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Mar 16 12:37:40 MDT 2012",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "We address the problem of externally measuring
                 aggregate functions over documents indexed by search
                 engines, like corpus size, index freshness, and density
                 of duplicates in the corpus. State of the art
                 estimators for such quantities [Bar-Yossef and Gurevich
                 2008b; Broder et al. 2006] are biased due to inaccurate
                 approximation of the so called `document degrees'. In
                 addition, the estimators in Bar-Yossef and Gurevich
                 [2008b] are quite costly, due to their reliance on
                 rejection sampling. We present new estimators that are
                 able to overcome the bias introduced by approximate
                 degrees. Our estimators are based on a careful
                 implementation of an approximate importance sampling
                 procedure. Comprehensive theoretical and empirical
                 analysis of the estimators demonstrates that they have
                 essentially no bias even in situations where document
                 degrees are poorly approximated. By avoiding the costly
                 rejection sampling approach, our new importance
                 sampling estimators are significantly more efficient
                 than the estimators proposed in Bar-Yossef and Gurevich
                 [2008b]. Furthermore, building on an idea from Broder
                 et al. [2006], we discuss Rao-Blackwellization as a
                 generic method for reducing variance in search engine
                 estimators. We show that Rao-Blackwellizing our
                 estimators results in performance improvements, without
                 compromising accuracy.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "18",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Gill:2011:COU,
  author =       "Phillipa Gill and Martin Arlitt and Niklas Carlsson
                 and Anirban Mahanti and Carey Williamson",
  title =        "Characterizing Organizational Use of {Web}-Based
                 Services: Methodology, Challenges, Observations, and
                 Insights",
  journal =      j-TWEB,
  volume =       "5",
  number =       "4",
  pages =        "19:1--19:??",
  month =        oct,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2019643.2019646",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Mar 16 12:37:40 MDT 2012",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Today's Web provides many different functionalities,
                 including communication, entertainment, social
                 networking, and information retrieval. In this article,
                 we analyze traces of HTTP activity from a large
                 enterprise and from a large university to identify and
                 characterize Web-based service usage. Our work provides
                 an initial methodology for the analysis of Web-based
                 services. While it is nontrivial to identify the
                 classes, instances, and providers for each transaction,
                 our results show that most of the traffic comes from a
                 small subset of providers, which can be classified
                 manually. Furthermore, we assess both qualitatively and
                 quantitatively how the Web has evolved over the past
                 decade, and discuss the implications of these
                 changes.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "19",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Singla:2011:CBC,
  author =       "Adish Singla and Ingmar Weber",
  title =        "Camera Brand Congruence and Camera Model Propagation
                 in the {Flickr} Social Graph",
  journal =      j-TWEB,
  volume =       "5",
  number =       "4",
  pages =        "20:1--20:??",
  month =        oct,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2019643.2019647",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Mar 16 12:37:40 MDT 2012",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Given that my friends on Flickr use cameras of brand
                 X, am I more likely to also use a camera of brand X?
                 Given that one of these friends changes her brand, am I
                 likely to do the same? Do new camera models pop up
                 uniformly in the friendship graph? Or do early adopters
                 then `convert' their friends? Which factors influence
                 the conversion probability of a user? These are the
                 kind of questions addressed in this work. Direct
                 applications involve personalized advertising in social
                 networks. For our study, we crawled a complete
                 connected component of the Flickr friendship graph with
                 a total of 67M edges and 3.9M users. 1.2M of these
                 users had at least one public photograph with valid
                 model metadata, which allowed us to assign camera
                 brands and models to users and time slots. Similarly,
                 we used, where provided in a user's profile,
                 information about a user's geographic location and the
                 groups joined on Flickr. Concerning brand congruence,
                 our main findings are the following. First, a pair of
                 friends on Flickr has a higher probability of being
                 congruent, that is, using the same brand, compared to
                 two random users (27\% vs. 19\%). Second, the degree of
                 congruence goes up for pairs of friends (i) in the same
                 country (29\%), (ii) who both only have very few
                 friends (30\%), and (iii) with a very high cliqueness
                 (38\%). Third, given that a user changes her camera
                 model between March-May 2007 and March-May 2008, high
                 cliqueness friends are more likely than random users to
                 do the same (54\% vs. 48\%). Fourth, users using
                 high-end cameras are far more loyal to their brand than
                 users using point-and-shoot cameras, with a probability
                 of staying with the same brand of 60\% vs 33\%, given
                 that a new camera is bought. Fifth, these `expert'
                 users' brand congruence reaches 66\% for high
                 cliqueness friends. All these differences are
                 statistically significant at 1\%. As for the
                 propagation of new models in the friendship graph, we
                 observe the following. First, the growth of connected
                 components of users converted to a particular, new
                 camera model differs distinctly from random growth.
                 Second, the decline of dissemination of a particular
                 model is close to random decline. This illustrates that
                 users influence their friends to change to a particular
                 new model, rather than from a particular old model.
                 Third, having many converted friends increases the
                 probability of the user to convert herself. Here
                 differences between friends from the same or from
                 different countries are more pronounced for
                 point-and-shoot than for digital single-lens reflex
                 users. Fourth, there was again a distinct difference
                 between arbitrary friends and high cliqueness friends
                 in terms of prediction quality for conversion.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "20",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Curlango-Rosas:2011:SSA,
  author =       "Cecilia Curlango-Rosas and Gregorio A. Ponce and
                 Gabriel A. Lopez-Morteo",
  title =        "A Specialized Search Assistant for Learning Objects",
  journal =      j-TWEB,
  volume =       "5",
  number =       "4",
  pages =        "21:1--21:??",
  month =        oct,
  year =         "2011",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2019643.2019648",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Mar 16 12:37:40 MDT 2012",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The Web holds a great quantity of material that can be
                 used to enhance classroom instruction. However, it is
                 not easy to retrieve this material with the search
                 engines currently available. This study produced a
                 specialized search assistant based on Google that
                 significantly increases the number of instances in
                 which teachers find the desired learning objects as
                 compared to using this popular public search engine
                 directly. Success in finding learning objects by study
                 participants went from 80\% using Google alone to 96\%
                 when using our search assistant in one scenario and, in
                 another scenario, from a 40\% success rate with Google
                 alone to 66\% with our assistant. This specialized
                 search assistant implements features such as bilingual
                 search and term suggestion which were requested by
                 teacher participants to help improve their searches.
                 Study participants evaluated the specialized search
                 assistant and found it significantly easier to use and
                 more useful than the popular search engine for the
                 purpose of finding learning objects.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "21",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Zhu:2012:CLS,
  author =       "Guangyu Zhu and Gilad Mishne",
  title =        "{ClickRank}: Learning Session-Context Models to Enrich
                 {Web} Search Ranking",
  journal =      j-TWEB,
  volume =       "6",
  number =       "1",
  pages =        "1:1--1:??",
  month =        mar,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2109205.2109206",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Mar 16 12:37:41 MDT 2012",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "User browsing information, particularly
                 non-search-related activity, reveals important
                 contextual information on the preferences and intents
                 of Web users. In this article, we demonstrate the
                 importance of mining general Web user behavior data to
                 improve ranking and other Web-search experience, with
                 an emphasis on analyzing individual user sessions for
                 creating aggregate models. In this context, we
                 introduce ClickRank, an efficient, scalable algorithm
                 for estimating Webpage and Website importance from
                 general Web user-behavior data. We lay out the
                 theoretical foundation of ClickRank based on an
                 intentional surfer model and discuss its properties. We
                 quantitatively evaluate its effectiveness regarding the
                 problem of Web-search ranking, showing that it
                 contributes significantly to retrieval performance as a
                 novel Web-search feature. We demonstrate that the
                 results produced by ClickRank for Web-search ranking
                 are highly competitive with those produced by other
                 approaches, yet achieved at better scalability and
                 substantially lower computational costs. Finally, we
                 discuss novel applications of ClickRank in providing
                 enriched user Web-search experience, highlighting the
                 usefulness of our approach for nonranking tasks.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "1",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Liu:2012:IWS,
  author =       "Yiqun Liu and Fei Chen and Weize Kong and Huijia Yu
                 and Min Zhang and Shaoping Ma and Liyun Ru",
  title =        "Identifying {Web} Spam with the Wisdom of the Crowds",
  journal =      j-TWEB,
  volume =       "6",
  number =       "1",
  pages =        "2:1--2:??",
  month =        mar,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2109205.2109207",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Mar 16 12:37:41 MDT 2012",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Combating Web spam has become one of the top
                 challenges for Web search engines. State-of-the-art
                 spam-detection techniques are usually designed for
                 specific, known types of Web spam and are incapable of
                 dealing with newly appearing spam types efficiently.
                 With user-behavior analyses from Web access logs, a
                 spam page-detection algorithm is proposed based on a
                 learning scheme. The main contributions are the
                 following. (1) User-visiting patterns of spam pages are
                 studied, and a number of user-behavior features are
                 proposed for separating Web spam pages from ordinary
                 pages. (2) A novel spam-detection framework is proposed
                 that can detect various kinds of Web spam, including
                 newly appearing ones, with the help of the
                 user-behavior analysis. Experiments on large-scale
                 practical Web access log data show the effectiveness of
                 the proposed features and the detection framework.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "2",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Mesbah:2012:CAB,
  author =       "Ali Mesbah and Arie van Deursen and Stefan Lenselink",
  title =        "Crawling {Ajax}-Based {Web} Applications through
                 Dynamic Analysis of User Interface State Changes",
  journal =      j-TWEB,
  volume =       "6",
  number =       "1",
  pages =        "3:1--3:??",
  month =        mar,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2109205.2109208",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Mar 16 12:37:41 MDT 2012",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Using JavaScript and dynamic DOM manipulation on the
                 client side of Web applications is becoming a
                 widespread approach for achieving rich interactivity
                 and responsiveness in modern Web applications. At the
                 same time, such techniques---collectively known as
                 Ajax---shatter the concept of webpages with unique
                 URLs, on which traditional Web crawlers are based. This
                 article describes a novel technique for crawling
                 Ajax-based applications through automatic dynamic
                 analysis of user-interface-state changes in Web
                 browsers. Our algorithm scans the DOM tree, spots
                 candidate elements that are capable of changing the
                 state, fires events on those candidate elements, and
                 incrementally infers a state machine that models the
                 various navigational paths and states within an Ajax
                 application. This inferred model can be used in program
                 comprehension and in analysis and testing of dynamic
                 Web states, for instance, or for generating a static
                 version of the application. In this article, we discuss
                 our sequential and concurrent Ajax crawling algorithms.
                 We present our open source tool called Crawljax, which
                 implements the concepts and algorithms discussed in
                 this article. Additionally, we report a number of
                 empirical studies in which we apply our approach to a
                 number of open-source and industrial Web applications
                 and elaborate on the obtained results.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "3",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Lauw:2012:QLO,
  author =       "Hady W. Lauw and Ee-Peng Lim and Ke Wang",
  title =        "Quality and Leniency in Online Collaborative Rating
                 Systems",
  journal =      j-TWEB,
  volume =       "6",
  number =       "1",
  pages =        "4:1--4:??",
  month =        mar,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2109205.2109209",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Mar 16 12:37:41 MDT 2012",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The emerging trend of social information processing
                 has resulted in Web users' increased reliance on
                 user-generated content contributed by others for
                 information searching and decision making. Rating
                 scores, a form of user-generated content contributed by
                 reviewers in online rating systems, allow users to
                 leverage others' opinions in the evaluation of objects.
                 In this article, we focus on the problem of summarizing
                 the rating scores given to an object into an overall
                 score that reflects the object's quality. We observe
                 that the existing approaches for summarizing scores
                 largely ignores the effect of reviewers exercising
                 different standards in assigning scores. Instead of
                 treating all reviewers as equals, our approach models
                 the leniency of reviewers, which refers to the tendency
                 of a reviewer to assign higher scores than other
                 coreviewers. Our approach is underlined by two
                 insights: (1) The leniency of a reviewer depends not
                 only on how the reviewer rates objects, but also on how
                 other reviewers rate those objects and (2) The leniency
                 of a reviewer and the quality of rated objects are
                 mutually dependent. We develop the leniency-aware
                 quality, or LQ model, which solves leniency and quality
                 simultaneously. We introduce both an exact and a ranked
                 solution to the model. Experiments on real-life and
                 synthetic datasets show that LQ is more effective than
                 comparable approaches. LQ is also shown to perform
                 consistently better under different parameter
                 settings.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "4",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Ashman:2012:E,
  author =       "Helen Ashman and Arun Iyengar and Marc Najork",
  title =        "Editorial",
  journal =      j-TWEB,
  volume =       "6",
  number =       "2",
  pages =        "5:1--5:??",
  month =        may,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2180861.2180862",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Nov 6 19:07:48 MST 2012",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "5",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{DeCapitaniDiVimercati:2012:ITM,
  author =       "Sabrina {De Capitani Di Vimercati} and Sara Foresti
                 and Sushil Jajodia and Stefano Paraboschi and Giuseppe
                 Psaila and Pierangela Samarati",
  title =        "Integrating trust management and access control in
                 data-intensive {Web} applications",
  journal =      j-TWEB,
  volume =       "6",
  number =       "2",
  pages =        "6:1--6:??",
  month =        may,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2180861.2180863",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Nov 6 19:07:48 MST 2012",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The widespread diffusion of Web-based services
                 provided by public and private organizations emphasizes
                 the need for a flexible solution for protecting the
                 information accessible through Web applications. A
                 promising approach is represented by credential-based
                 access control and trust management. However, although
                 much research has been done and several proposals
                 exist, a clear obstacle to the realization of their
                 benefits in data-intensive Web applications is
                 represented by the lack of adequate support in the
                 DBMSs. As a matter of fact, DBMSs are often responsible
                 for the management of most of the information that is
                 accessed using a Web browser or a Web service
                 invocation. In this article, we aim at eliminating this
                 gap, and present an approach integrating trust
                 management with the access control of the DBMS. We
                 propose a trust model with a SQL syntax and illustrate
                 an algorithm for the efficient verification of a
                 delegation path for certificates. Our solution nicely
                 complements current trust management proposals allowing
                 the efficient realization of the services of an
                 advanced trust management model within current
                 relational DBMSs. An important benefit of our approach
                 lies in its potential for a robust end-to-end design of
                 security for personal data in Web scenario, where
                 vulnerabilities of Web applications cannot be used to
                 violate the protection of the data residing on the
                 database server. We also illustrate the implementation
                 of our approach within an open-source DBMS discussing
                 design choices and performance impact.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "6",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Alrifai:2012:HAE,
  author =       "Mohammad Alrifai and Thomas Risse and Wolfgang Nejdl",
  title =        "A hybrid approach for efficient {Web} service
                 composition with end-to-end {QoS} constraints",
  journal =      j-TWEB,
  volume =       "6",
  number =       "2",
  pages =        "7:1--7:??",
  month =        may,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2180861.2180864",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Nov 6 19:07:48 MST 2012",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Dynamic selection of Web services at runtime is
                 important for building flexible and loosely-coupled
                 service-oriented applications. An abstract description
                 of the required services is provided at design-time,
                 and matching service offers are located at runtime.
                 With the growing number of Web services that provide
                 the same functionality but differ in quality parameters
                 (e.g., availability, response time), a decision needs
                 to be made on which services should be selected such
                 that the user's end-to-end QoS requirements are
                 satisfied. Although very efficient, local selection
                 strategy fails short in handling global QoS
                 requirements. Solutions based on global optimization,
                 on the other hand, can handle global constraints, but
                 their poor performance renders them inappropriate for
                 applications with dynamic and realtime requirements. In
                 this article we address this problem and propose a
                 hybrid solution that combines global optimization with
                 local selection techniques to benefit from the
                 advantages of both worlds. The proposed solution
                 consists of two steps: first, we use mixed integer
                 programming (MIP) to find the optimal decomposition of
                 global QoS constraints into local constraints. Second,
                 we use distributed local selection to find the best Web
                 services that satisfy these local constraints. The
                 results of experimental evaluation indicate that our
                 approach significantly outperforms existing solutions
                 in terms of computation time while achieving
                 close-to-optimal results.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "7",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Desnoyers:2012:MAM,
  author =       "Peter Desnoyers and Timothy Wood and Prashant Shenoy
                 and Rahul Singh and Sangameshwar Patil and Harrick
                 Vin",
  title =        "{Modellus}: Automated modeling of complex {Internet}
                 data center applications",
  journal =      j-TWEB,
  volume =       "6",
  number =       "2",
  pages =        "8:1--8:??",
  month =        may,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2180861.2180865",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Nov 6 19:07:48 MST 2012",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The rising complexity of distributed server
                 applications in Internet data centers has made the
                 tasks of modeling and analyzing their behavior
                 increasingly difficult. This article presents Modellus,
                 a novel system for automated modeling of complex
                 web-based data center applications using methods from
                 queuing theory, data mining, and machine learning.
                 Modellus uses queuing theory and statistical methods to
                 automatically derive models to predict the resource
                 usage of an application and the workload it triggers;
                 these models can be composed to capture multiple
                 dependencies between interacting applications. Model
                 accuracy is maintained by fast, distributed testing,
                 automated relearning of models when they change, and
                 methods to bound prediction errors in composite models.
                 We have implemented a prototype of Modellus, deployed
                 it on a data center testbed, and evaluated its efficacy
                 for modeling and analysis of several distributed
                 multitier web applications. Our results show that this
                 feature-based modeling technique is able to make
                 predictions across several data center tiers, and
                 maintain predictive accuracy (typically 95\% or better)
                 in the face of significant shifts in workload
                 composition; we also demonstrate practical applications
                 of the Modellus system to prediction and provisioning
                 of real-world data center applications.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "8",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Aiello:2012:FPH,
  author =       "Luca Maria Aiello and Alain Barrat and Rossano
                 Schifanella and Ciro Cattuto and Benjamin Markines and
                 Filippo Menczer",
  title =        "Friendship prediction and homophily in social media",
  journal =      j-TWEB,
  volume =       "6",
  number =       "2",
  pages =        "9:1--9:??",
  month =        may,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2180861.2180866",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Nov 6 19:07:48 MST 2012",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Social media have attracted considerable attention
                 because their open-ended nature allows users to create
                 lightweight semantic scaffolding to organize and share
                 content. To date, the interplay of the social and
                 topical components of social media has been only
                 partially explored. Here, we study the presence of
                 homophily in three systems that combine tagging social
                 media with online social networks. We find a
                 substantial level of topical similarity among users who
                 are close to each other in the social network. We
                 introduce a null model that preserves user activity
                 while removing local correlations, allowing us to
                 disentangle the actual local similarity between users
                 from statistical effects due to the assortative mixing
                 of user activity and centrality in the social network.
                 This analysis suggests that users with similar
                 interests are more likely to be friends, and therefore
                 topical similarity measures among users based solely on
                 their annotation metadata should be predictive of
                 social links. We test this hypothesis on several
                 datasets, confirming that social networks constructed
                 from topical similarity capture actual friendship
                 accurately. When combined with topological features,
                 topical similarity achieves a link prediction accuracy
                 of about 92\%.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "9",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Comai:2012:MDM,
  author =       "Sara Comai and Davide Mazza",
  title =        "A model-driven methodology to the content layout
                 problem in {Web} applications",
  journal =      j-TWEB,
  volume =       "6",
  number =       "3",
  pages =        "10:1--10:38",
  month =        sep,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2344416.2344417",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Nov 6 19:07:49 MST 2012",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/texbook3.bib;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "This article presents a model-driven approach for the
                 design of the layout in a complex Web application,
                 where large amounts of data are accessed. The aim of
                 this work is to reduce, as much as possible, repetitive
                 tasks and to factor out common aspects into different
                 kinds of rules that can be reused across different
                 applications. In particular, exploiting the conceptual
                 elements of the typical models used for the design of a
                 Web application, it defines presentation and layout
                 rules at different levels of abstraction and
                 granularity. A procedure for the automatic layout of
                 the content of a page is proposed and evaluated, and
                 the layout of advanced Web applications is discussed.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "10",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "Automatic contents layout; graphical visualization and
                 rendering; Web applications design",
}

@Article{Merhav:2012:EIN,
  author =       "Yuval Merhav and Filipe Mesquita and Denilson Barbosa
                 and Wai Gen Yee and Ophir Frieder",
  title =        "Extracting information networks from the blogosphere",
  journal =      j-TWEB,
  volume =       "6",
  number =       "3",
  pages =        "11:1--11:??",
  month =        sep,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2344416.2344418",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Nov 6 19:07:49 MST 2012",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "We study the problem of automatically extracting
                 information networks formed by recognizable entities as
                 well as relations among them from social media sites.
                 Our approach consists of using state-of-the-art natural
                 language processing tools to identify entities and
                 extract sentences that relate such entities, followed
                 by using text-clustering algorithms to identify the
                 relations within the information network. We propose a
                 new term-weighting scheme that significantly improves
                 on the state-of-the-art in the task of relation
                 extraction, both when used in conjunction with the
                 standard tf $ \cdot $ idf scheme and also when used as
                 a pruning filter. We describe an effective method for
                 identifying benchmarks for open information extraction
                 that relies on a curated online database that is
                 comparable to the hand-crafted evaluation datasets in
                 the literature. From this benchmark, we derive a much
                 larger dataset which mimics realistic conditions for
                 the task of open information extraction. We report on
                 extensive experiments on both datasets, which not only
                 shed light on the accuracy levels achieved by
                 state-of-the-art open information extraction tools, but
                 also on how to tune such tools for better results.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "11",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Miliaraki:2012:FDS,
  author =       "Iris Miliaraki and Manolis Koubarakis",
  title =        "{FoXtrot}: Distributed structural and value {XML}
                 filtering",
  journal =      j-TWEB,
  volume =       "6",
  number =       "3",
  pages =        "12:1--12:??",
  month =        sep,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2344416.2344419",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Nov 6 19:07:49 MST 2012",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Publish/subscribe systems have emerged in recent years
                 as a promising paradigm for offering various popular
                 notification services. In this context, many XML
                 filtering systems have been proposed to efficiently
                 identify XML data that matches user interests expressed
                 as queries in an XML query language like XPath.
                 However, in order to offer XML filtering functionality
                 on an Internet-scale, we need to deploy such a service
                 in a distributed environment, avoiding bottlenecks that
                 can deteriorate performance. In this work, we design
                 and implement FoXtrot, a system for filtering XML data
                 that combines the strengths of automata for efficient
                 filtering and distributed hash tables for building a
                 fully distributed system. Apart from
                 structural-matching, performed using automata, we also
                 discuss different methods for evaluating value-based
                 predicates. We perform an extensive experimental
                 evaluation of our system, FoXtrot, on a local cluster
                 and on the PlanetLab network and demonstrate that it
                 can index millions of user queries, achieving a high
                 indexing and filtering throughput. At the same time,
                 FoXtrot exhibits very good load-balancing properties
                 and improves its performance as we increase the size of
                 the network.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "12",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Dork:2012:NTW,
  author =       "Marian D{\"o}rk and Carey Williamson and Sheelagh
                 Carpendale",
  title =        "Navigating tomorrow's web: From searching and browsing
                 to visual exploration",
  journal =      j-TWEB,
  volume =       "6",
  number =       "3",
  pages =        "13:1--13:??",
  month =        sep,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2344416.2344420",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Nov 6 19:07:49 MST 2012",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "We propose a new way of navigating the Web using
                 interactive information visualizations, and present
                 encouraging results from a large-scale Web study of a
                 visual exploration system. While the Web has become an
                 immense, diverse information space, it has also evolved
                 into a powerful software platform. We believe that the
                 established interaction techniques of searching and
                 browsing do not sufficiently utilize these advances,
                 since information seekers have to transform their
                 information needs into specific, text-based search
                 queries resulting in mostly text-based lists of
                 resources. In contrast, we foresee a new type of
                 information seeking that is high-level and more
                 engaging, by providing the information seeker with
                 interactive visualizations that give graphical
                 overviews and enable query formulation. Building on
                 recent work on faceted navigation, information
                 visualization, and exploratory search, we conceptualize
                 this type of information navigation as visual
                 exploration and evaluate a prototype Web-based system
                 that implements it. We discuss the results of a
                 large-scale, mixed-method Web study that provides a
                 better understanding of the potential benefits of
                 visual exploration on the Web, and its particular
                 performance challenges.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "13",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Cambazoglu:2012:CBQ,
  author =       "B. Barla Cambazoglu and Ismail Sengor Altingovde and
                 Rifat Ozcan and {\"O}zg{\"u}r Ulusoy",
  title =        "Cache-Based Query Processing for Search Engines",
  journal =      j-TWEB,
  volume =       "6",
  number =       "4",
  pages =        "14:1--14:??",
  month =        nov,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2382616.2382617",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sun May 5 09:27:25 MDT 2013",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "In practice, a search engine may fail to serve a query
                 due to various reasons such as hardware/network
                 failures, excessive query load, lack of matching
                 documents, or service contract limitations (e.g., the
                 query rate limits for third-party users of a search
                 service). In this kind of scenarios, where the backend
                 search system is unable to generate answers to queries,
                 approximate answers can be generated by exploiting the
                 previously computed query results available in the
                 result cache of the search engine. In this work, we
                 propose two alternative strategies to implement this
                 cache-based query processing idea. The first strategy
                 aggregates the results of similar queries that are
                 previously cached in order to create synthetic results
                 for new queries. The second strategy forms an inverted
                 index over the textual information (i.e., query terms
                 and result snippets) present in the result cache and
                 uses this index to answer new queries. Both approaches
                 achieve reasonable result qualities compared to
                 processing queries with an inverted index built on the
                 collection.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "14",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Delac:2012:MSS,
  author =       "Goran Delac and Ivan Budiselic and Ivan Zuzak and Ivan
                 Skuliber and Tomislav Stefanec",
  title =        "A Methodology for {SIP} and {SOAP} Integration Using
                 Application-Specific Protocol Conversion",
  journal =      j-TWEB,
  volume =       "6",
  number =       "4",
  pages =        "15:1--15:??",
  month =        nov,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2382616.2382618",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sun May 5 09:27:25 MDT 2013",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "In recent years, the ubiquitous demands for
                 cross-protocol application access are driving the need
                 for deeper integration between SIP and SOAP. In this
                 article we present a novel methodology for integrating
                 these two protocols. Through an analysis of properties
                 of SIP and SOAP we show that integration between these
                 protocols should be based on application-specific
                 converters. We describe a generic SIP/SOAP gateway that
                 implements message handling and network and storage
                 management while relying on application-specific
                 converters to define session management and message
                 mapping for a specific set of SIP and SOAP
                 communication nodes. In order to ease development of
                 these converters, we introduce an XML-based
                 domain-specific language for describing
                 application-specific conversion processes. We show how
                 conversion processes can be easily specified in the
                 language using message sequence diagrams of the desired
                 interaction. We evaluate the presented methodology
                 through performance analysis of the developed prototype
                 gateway and high-level comparison with other
                 solutions.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "15",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Jeon:2012:WCP,
  author =       "Myeongjae Jeon and Youngjae Kim and Jeaho Hwang and
                 Joonwon Lee and Euiseong Seo",
  title =        "Workload Characterization and Performance Implications
                 of Large-Scale Blog Servers",
  journal =      j-TWEB,
  volume =       "6",
  number =       "4",
  pages =        "16:1--16:??",
  month =        nov,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2382616.2382619",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sun May 5 09:27:25 MDT 2013",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "With the ever-increasing popularity of Social Network
                 Services (SNSs), an understanding of the
                 characteristics of these services and their effects on
                 the behavior of their host servers is critical.
                 However, there has been a lack of research on the
                 workload characterization of servers running SNS
                 applications such as blog services. To fill this void,
                 we empirically characterized real-world Web server logs
                 collected from one of the largest South Korean blog
                 hosting sites for 12 consecutive days. The logs consist
                 of more than 96 million HTTP requests and 4.7TB of
                 network traffic. Our analysis reveals the following:
                 (i) The transfer size of nonmultimedia files and blog
                 articles can be modeled using a truncated Pareto
                 distribution and a log-normal distribution,
                 respectively; (ii) user access for blog articles does
                 not show temporal locality, but is strongly biased
                 towards those posted with image or audio files. We
                 additionally discuss the potential performance
                 improvement through clustering of small files on a blog
                 page into contiguous disk blocks, which benefits from
                 the observed file access patterns. Trace-driven
                 simulations show that, on average, the suggested
                 approach achieves 60.6\% better system throughput and
                 reduces the processing time for file access by 30.8\%
                 compared to the best performance of the Ext4
                 filesystem.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "16",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Wilson:2012:BSG,
  author =       "Christo Wilson and Alessandra Sala and Krishna P. N.
                 Puttaswamy and Ben Y. Zhao",
  title =        "Beyond Social Graphs: User Interactions in Online
                 Social Networks and their Implications",
  journal =      j-TWEB,
  volume =       "6",
  number =       "4",
  pages =        "17:1--17:??",
  month =        nov,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2382616.2382620",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sun May 5 09:27:25 MDT 2013",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Social networks are popular platforms for interaction,
                 communication, and collaboration between friends.
                 Researchers have recently proposed an emerging class of
                 applications that leverage relationships from social
                 networks to improve security and performance in
                 applications such as email, Web browsing, and overlay
                 routing. While these applications often cite social
                 network connectivity statistics to support their
                 designs, researchers in psychology and sociology have
                 repeatedly cast doubt on the practice of inferring
                 meaningful relationships from social network
                 connections alone. This leads to the question: ``Are
                 social links valid indicators of real user interaction?
                 If not, then how can we quantify these factors to form
                 a more accurate model for evaluating socially enhanced
                 applications?'' In this article, we address this
                 question through a detailed study of user interactions
                 in the Facebook social network. We propose the use of
                 ``interaction graphs'' to impart meaning to online
                 social links by quantifying user interactions. We
                 analyze interaction graphs derived from Facebook user
                 traces and show that they exhibit significantly lower
                 levels of the ``small-world'' properties present in
                 their social graph counterparts. This means that these
                 graphs have fewer ``supernodes'' with extremely high
                 degree, and overall graph diameter increases
                 significantly as a result. To quantify the impact of
                 our observations, we use both types of graphs to
                 validate several well-known social-based applications
                 that rely on graph properties to infuse new
                 functionality into Internet applications, including
                 Reliable Email (RE), SybilGuard, and the weighted
                 cascade influence maximization algorithm. The results
                 reveal new insights into each of these systems, and
                 confirm our hypothesis that to obtain realistic and
                 accurate results, ongoing research on social network
                 applications studies of social applications should use
                 real indicators of user interactions in lieu of social
                 graphs.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "17",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Weerkamp:2012:EEC,
  author =       "Wouter Weerkamp and Krisztian Balog and Maarten de
                 Rijke",
  title =        "Exploiting External Collections for Query Expansion",
  journal =      j-TWEB,
  volume =       "6",
  number =       "4",
  pages =        "18:1--18:??",
  month =        nov,
  year =         "2012",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2382616.2382621",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sun May 5 09:27:25 MDT 2013",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "A persisting challenge in the field of information
                 retrieval is the vocabulary mismatch between a user's
                 information need and the relevant documents. One way of
                 addressing this issue is to apply query modeling: to
                 add terms to the original query and reweigh the terms.
                 In social media, where documents usually contain
                 creative and noisy language (e.g., spelling and
                 grammatical errors), query modeling proves difficult.
                 To address this, attempts to use external sources for
                 query modeling have been made and seem to be
                 successful. In this article we propose a general
                 generative query expansion model that uses external
                 document collections for term generation: the External
                 Expansion Model (EEM). The main rationale behind our
                 model is our hypothesis that each query requires its
                 own mixture of external collections for expansion and
                 that an expansion model should account for this. For
                 some queries we expect, for example, a news collection
                 to be most beneficial, while for other queries we could
                 benefit more by selecting terms from a general
                 encyclopedia. EEM allows for query-dependent weighing
                 of the external collections. We put our model to the
                 test on the task of blog post retrieval and we use four
                 external collections in our experiments: (i) a news
                 collection, (ii) a Web collection, (iii) Wikipedia, and
                 (iv) a blog post collection. Experiments show that EEM
                 outperforms query expansion on the individual
                 collections, as well as the Mixture of Relevance Models
                 that was previously proposed by Diaz and Metzler
                 [2006]. Extensive analysis of the results shows that
                 our naive approach to estimating query-dependent
                 collection importance works reasonably well and that,
                 when we use ``oracle'' settings, we see the full
                 potential of our model. We also find that the
                 query-dependent collection importance has more impact
                 on retrieval performance than the independent
                 collection importance (i.e., a collection prior).",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "18",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Wu:2013:MVC,
  author =       "Ou Wu and Weiming Hu and Lei Shi",
  title =        "Measuring the Visual Complexities of {Web} Pages",
  journal =      j-TWEB,
  volume =       "7",
  number =       "1",
  pages =        "1:1--1:??",
  month =        mar,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2435215.2435216",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sun May 5 09:27:25 MDT 2013",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Visual complexities (VisComs) of Web pages
                 significantly affect user experience, and automatic
                 evaluation can facilitate a large number of Web-based
                 applications. The construction of a model for measuring
                 the VisComs of Web pages requires the extraction of
                 typical features and learning based on labeled Web
                 pages. However, as far as the authors are aware, little
                 headway has been made on measuring VisCom in Web mining
                 and machine learning. The present article provides a
                 new approach combining Web mining techniques and
                 machine learning algorithms for measuring the VisComs
                 of Web pages. The structure of a Web page is first
                 analyzed, and the layout is then extracted. Using a Web
                 page as a semistructured image, three classes of
                 features are extracted to construct a feature vector.
                 The feature vector is fed into a learned measuring
                 function to calculate the VisCom of the page. In the
                 proposed approach of the present study, the type of the
                 measuring function and its learning depend on the
                 quantification strategy for VisCom. Aside from using a
                 category and a score to represent VisCom as existing
                 work, this study presents a new strategy utilizing a
                 distribution to quantify the VisCom of a Web page.
                 Empirical evaluation suggests the effectiveness of the
                 proposed approach in terms of both features and
                 learning algorithms.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "1",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Hanson:2013:PWA,
  author =       "Vicki L. Hanson and John T. Richards",
  title =        "Progress on {Website} Accessibility?",
  journal =      j-TWEB,
  volume =       "7",
  number =       "1",
  pages =        "2:1--2:??",
  month =        mar,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2435215.2435217",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sun May 5 09:27:25 MDT 2013",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Over 100 top-traffic and government websites from the
                 United States and United Kingdom were examined for
                 evidence of changes on accessibility indicators over
                 the 14-year period from 1999 to 2012, the longest
                 period studied to date. Automated analyses of WCAG 2.0
                 Level A Success Criteria found high percentages of
                 violations overall. Unlike more circumscribed studies,
                 however, these sites exhibited improvements over the
                 years on a number of accessibility indicators, with
                 government sites being less likely than topsites to
                 have accessibility violations. Examination of the
                 causes of success and failure suggests that improving
                 accessibility may be due, in part, to changes in
                 website technologies and coding practices rather than a
                 focus on accessibility per se.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "2",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Baykan:2013:CST,
  author =       "Eda Baykan and Monika Henzinger and Ingmar Weber",
  title =        "A Comprehensive Study of Techniques for {URL}-Based
                 {Web} Page Language Classification",
  journal =      j-TWEB,
  volume =       "7",
  number =       "1",
  pages =        "3:1--3:??",
  month =        mar,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2435215.2435218",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sun May 5 09:27:25 MDT 2013",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Given only the URL of a Web page, can we identify its
                 language? In this article we examine this question.
                 URL-based language classification is useful when the
                 content of the Web page is not available or downloading
                 the content is a waste of bandwidth and time. We built
                 URL-based language classifiers for English, German,
                 French, Spanish, and Italian by applying a variety of
                 algorithms and features. As algorithms we used machine
                 learning algorithms which are widely applied for text
                 classification and state-of-art algorithms for language
                 identification of text. As features we used words,
                 various sized n-grams, and custom-made features (our
                 novel feature set). We compared our approaches with two
                 baseline methods, namely classification by country code
                 top-level domains and classification by IP addresses of
                 the hosting Web servers. We trained and tested our
                 classifiers in a 10-fold cross-validation setup on a
                 dataset obtained from the Open Directory Project and
                 from querying a commercial search engine. We obtained
                 the lowest F1-measure for English (94) and the highest
                 F1-measure for German (98) with the best performing
                 classifiers. We also evaluated the performance of our
                 methods: (i) on a set of Web pages written in Adobe
                 Flash and (ii) as part of a language-focused crawler.
                 In the first case, the content of the Web page is hard
                 to extract and in the second page downloading pages of
                 the ``wrong'' language constitutes a waste of
                 bandwidth. In both settings the best classifiers have a
                 high accuracy with an F1-measure between 95 (for
                 English) and 98 (for Italian) for the Adobe Flash pages
                 and a precision between 90 (for Italian) and 97 (for
                 French) for the language-focused crawler.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "3",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Marriott:2013:HAT,
  author =       "Kim Marriott and Peter Moulder and Nathan Hurst",
  title =        "{HTML} Automatic Table Layout",
  journal =      j-TWEB,
  volume =       "7",
  number =       "1",
  pages =        "4:1--4:??",
  month =        mar,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2435215.2435219",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sun May 5 09:27:25 MDT 2013",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Automatic layout of tables is required in online
                 applications because of the need to tailor the layout
                 to the viewport width, choice of font, and dynamic
                 content. However, if the table contains text,
                 minimizing the height of the table for a fixed maximum
                 width is NP-hard. Thus, more efficient heuristic
                 algorithms are required. We evaluate the HTML table
                 layout recommendation and find that while it generally
                 produces quite compact layout it is brittle and can
                 lead to quite uncompact layout. We present an alternate
                 heuristic algorithm. It uses a greedy strategy that
                 starts from the widest reasonable layout and repeatedly
                 chooses to narrow the column for which narrowing leads
                 to the least increase in table height. The algorithm is
                 simple, fast enough to be used in online applications,
                 and gives significantly more compact layout than is
                 obtained with HTML's recommended table layout
                 algorithm.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "4",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Anisetti:2013:TBS,
  author =       "Marco Anisetti and Claudio A. Ardagna and Ernesto
                 Damiani and Francesco Saonara",
  title =        "A test-based security certification scheme for {Web}
                 services",
  journal =      j-TWEB,
  volume =       "7",
  number =       "2",
  pages =        "5:1--5:??",
  month =        may,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2460383.2460384",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:18 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The Service-Oriented Architecture (SOA) paradigm is
                 giving rise to a new generation of applications built
                 by dynamically composing loosely coupled autonomous
                 services. Clients (i.e., software agents acting on
                 behalf of human users or service providers)
                 implementing such complex applications typically search
                 and integrate services on the basis of their functional
                 requirements and of their trust in the service
                 suppliers. A major issue in this scenario relates to
                 the definition of an assurance technique allowing
                 clients to select services on the basis of their
                 nonfunctional requirements and increasing their
                 confidence that the selected services will satisfy such
                 requirements. In this article, we first present an
                 assurance solution that focuses on security and
                 supports a test-based security certification scheme for
                 Web services. The certification scheme is driven by the
                 security properties to be certified and relies upon a
                 formal definition of the service model. The evidence
                 supporting a certified property is computed using a
                 model-based testing approach that, starting from the
                 service model, automatically generates the test cases
                 to be used in the service certification. We also define
                 a set of indexes and metrics that evaluate the
                 assurance level and the quality of the certification
                 process. Finally, we present our evaluation toolkit and
                 experimental results obtained applying our
                 certification solution to a financial service
                 implementing the Interactive Financial eXchange (IFX)
                 standard.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "5",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Victor:2013:ETB,
  author =       "Patricia Victor and Nele Verbiest and Chris Cornelis
                 and Martine {De Cock}",
  title =        "Enhancing the trust-based recommendation process with
                 explicit distrust",
  journal =      j-TWEB,
  volume =       "7",
  number =       "2",
  pages =        "6:1--6:??",
  month =        may,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2460383.2460385",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:18 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "When a Web application with a built-in recommender
                 offers a social networking component which enables its
                 users to form a trust network, it can generate more
                 personalized recommendations by combining user ratings
                 with information from the trust network. These are the
                 so-called trust-enhanced recommendation systems. While
                 research on the incorporation of trust for
                 recommendations is thriving, the potential of
                 explicitly stated distrust remains almost unexplored.
                 In this article, we introduce a distrust-enhanced
                 recommendation algorithm which has its roots in
                 Golbeck's trust-based weighted mean. Through
                 experiments on a set of reviews from Epinions.com, we
                 show that our new algorithm outperforms its standard
                 trust-only counterpart with respect to accuracy,
                 thereby demonstrating the positive effect that explicit
                 distrust can have on trust-based recommendations.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "6",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Yue:2013:MSI,
  author =       "Chuan Yue and Haining Wang",
  title =        "A measurement study of insecure {JavaScript} practices
                 on the {Web}",
  journal =      j-TWEB,
  volume =       "7",
  number =       "2",
  pages =        "7:1--7:??",
  month =        may,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2460383.2460386",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:18 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/java2010.bib;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "JavaScript is an interpreted programming language most
                 often used for enhancing webpage interactivity and
                 functionality. It has powerful capabilities to interact
                 with webpage documents and browser windows, however, it
                 has also opened the door for many browser-based
                 security attacks. Insecure engineering practices of
                 using JavaScript may not directly lead to security
                 breaches, but they can create new attack vectors and
                 greatly increase the risks of browser-based attacks. In
                 this article, we present the first measurement study on
                 insecure practices of using JavaScript on the Web. Our
                 focus is on the insecure practices of JavaScript
                 inclusion and dynamic generation, and we examine their
                 severity and nature on 6,805 unique websites. Our
                 measurement results reveal that insecure JavaScript
                 practices are common at various websites: (1) at least
                 66.4\% of the measured websites manifest the insecure
                 practices of including JavaScript files from external
                 domains into the top-level documents of their webpages;
                 (2) over 44.4\% of the measured websites use the
                 dangerous eval() function to dynamically generate and
                 execute JavaScript code on their webpages; and (3) in
                 JavaScript dynamic generation, using the
                 document.write() method and the innerHTML property is
                 much more popular than using the relatively secure
                 technique of creating script elements via DOM methods.
                 Our analysis indicates that safe alternatives to these
                 insecure practices exist in common cases and ought to
                 be adopted by website developers and administrators for
                 reducing potential security risks.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "7",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Su:2013:UQI,
  author =       "Weifeng Su and Hejun Wu and Yafei Li and Jing Zhao and
                 Frederick H. Lochovsky and Hongmin Cai and Tianqiang
                 Huang",
  title =        "Understanding query interfaces by statistical
                 parsing",
  journal =      j-TWEB,
  volume =       "7",
  number =       "2",
  pages =        "8:1--8:??",
  month =        may,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2460383.2460387",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:18 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Users submit queries to an online database via its
                 query interface. Query interface parsing, which is
                 important for many applications, understands the query
                 capabilities of a query interface. Since most query
                 interfaces are organized hierarchically, we present a
                 novel query interface parsing method, StatParser
                 (Statistical Parser), to automatically extract the
                 hierarchical query capabilities of query interfaces.
                 StatParser automatically learns from a set of parsed
                 query interfaces and parses new query interfaces.
                 StatParser starts from a small grammar and enhances the
                 grammar with a set of probabilities learned from parsed
                 query interfaces under the maximum-entropy principle.
                 Given a new query interface, the probability-enhanced
                 grammar identifies the parse tree with the largest
                 global probability to be the query capabilities of the
                 query interface. Experimental results show that
                 StatParser very accurately extracts the query
                 capabilities and can effectively overcome the problems
                 of existing query interface parsers.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "8",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Diaz:2013:LEU,
  author =       "Oscar D{\'\i}az and Crist{\'o}bal Arellano and Maider
                 Azanza",
  title =        "A language for end-user {Web} augmentation: Caring for
                 producers and consumers alike",
  journal =      j-TWEB,
  volume =       "7",
  number =       "2",
  pages =        "9:1--9:??",
  month =        may,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2460383.2460388",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:18 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/java2010.bib;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Web augmentation is to the Web what augmented reality
                 is to the physical world: layering relevant
                 content/layout/navigation over the existing Web to
                 customize the user experience. This is achieved through
                 JavaScript (JS) using browser weavers (e.g.,
                 Greasemonkey). To date, over 43 million of downloads of
                 Greasemonkey scripts ground the vitality of this
                 movement. However, Web augmentation is hindered by
                 being programming intensive and prone to malware. This
                 prevents end-users from participating as both producers
                 and consumers of scripts: producers need to know JS,
                 consumers need to trust JS. This article aims at
                 promoting end-user participation in both roles. The
                 vision is for end-users to prosume (the act of
                 simultaneously caring for producing and consuming)
                 scripts as easily as they currently prosume their
                 pictures or videos. Encouraging production requires
                 more ``natural'' and abstract constructs. Promoting
                 consumption calls for augmentation scripts to be easier
                 to understand, share, and trust upon. To this end, we
                 explore the use of Domain-Specific Languages (DSLs) by
                 introducing Sticklet. Sticklet is an internal DSL on
                 JS, where JS generality is reduced for the sake of
                 learnability and reliability. Specifically, Web
                 augmentation is conceived as fixing in existing web
                 sites (i.e., the wall ) HTML fragments extracted from
                 either other sites or Web services (i.e., the stickers
                 ). Sticklet targets hobby programmers as producers, and
                 computer literates as consumers. From a producer
                 perspective, benefits are threefold. As a restricted
                 grammar on top of JS, Sticklet expressions are domain
                 oriented and more declarative than their JS
                 counterparts, hence speeding up development. As
                 syntactically correct JS expressions, Sticklet scripts
                 can be installed as traditional scripts and hence,
                 programmers can continue using existing JS tools. As
                 declarative expressions, they are easier to maintain,
                 and amenable for optimization. From a consumer
                 perspective, domain specificity brings
                 understandability (due to declarativeness), reliability
                 (due to built-in security), and ``consumability''
                 (i.e., installation/enactment/sharing of Sticklet
                 expressions are tuned to the shortage of time and
                 skills of the target audience). Preliminary evaluations
                 indicate that 77\% of the subjects were able to develop
                 new Sticklet scripts in less than thirty minutes while
                 84\% were able to consume these scripts in less than
                 ten minutes. Sticklet is available to download as a
                 Mozilla add-on.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "9",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Kaldeli:2013:CWS,
  author =       "Eirini Kaldeli and Ehsan Ullah Warriach and Alexander
                 Lazovik and Marco Aiello",
  title =        "Coordinating the web of services for a smart home",
  journal =      j-TWEB,
  volume =       "7",
  number =       "2",
  pages =        "10:1--10:??",
  month =        may,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2460383.2460389",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:18 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Domotics, concerned with the realization of
                 intelligent home environments, is a novel field which
                 can highly benefit from solutions inspired by
                 service-oriented principles to enhance the convenience
                 and security of modern home residents. In this work, we
                 present an architecture for a smart home, starting from
                 the lower device interconnectivity level up to the
                 higher application layers that undertake the load of
                 complex functionalities and provide a number of
                 services to end-users. We claim that in order for smart
                 homes to exhibit a genuinely intelligent behavior, the
                 ability to compute compositions of individual devices
                 automatically and dynamically is paramount. To this
                 end, we incorporate into the architecture a composition
                 component that employs artificial intelligence
                 domain-independent planning to generate compositions at
                 runtime, in a constantly evolving environment. We have
                 implemented a fully working prototype that realizes
                 such an architecture, and have evaluated it both in
                 terms of performance as well as from the end-user point
                 of view. The results of the evaluation show that the
                 service-oriented architectural design and the support
                 for dynamic compositions is quite efficient from the
                 technical point of view, and that the system succeeds
                 in satisfying the expectations and objectives of the
                 users.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "10",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Balakrishnan:2013:ART,
  author =       "Raju Balakrishnan and Subbarao Kambhampati and
                 Manishkumar Jha",
  title =        "Assessing relevance and trust of the deep web sources
                 and results based on inter-source agreement",
  journal =      j-TWEB,
  volume =       "7",
  number =       "2",
  pages =        "11:1--11:??",
  month =        may,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2460383.2460390",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:18 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Deep web search engines face the formidable challenge
                 of retrieving high-quality results from the vast
                 collection of searchable databases. Deep web search is
                 a two-step process of selecting the high-quality
                 sources and ranking the results from the selected
                 sources. Though there are existing methods for both the
                 steps, they assess the relevance of the sources and the
                 results using the query-result similarity. When applied
                 to the deep web these methods have two deficiencies.
                 First is that they are agnostic to the correctness
                 (trustworthiness) of the results. Second, the
                 query-based relevance does not consider the importance
                 of the results and sources. These two considerations
                 are essential for the deep web and open collections in
                 general. Since a number of deep web sources provide
                 answers to any query, we conjuncture that the
                 agreements between these answers are helpful in
                 assessing the importance and the trustworthiness of the
                 sources and the results. For assessing source quality,
                 we compute the agreement between the sources as the
                 agreement of the answers returned. While computing the
                 agreement, we also measure and compensate for the
                 possible collusion between the sources. This adjusted
                 agreement is modeled as a graph with sources at the
                 vertices. On this agreement graph, a quality score of a
                 source, that we call SourceRank, is calculated as the
                 stationary visit probability of a random walk. For
                 ranking results, we analyze the second-order agreement
                 between the results. Further extending SourceRank to
                 multidomain search, we propose a source ranking
                 sensitive to the query domains. Multiple
                 domain-specific rankings of a source are computed, and
                 these ranks are combined for the final ranking. We
                 perform extensive evaluations on online and hundreds of
                 Google Base sources spanning across domains. The
                 proposed result and source rankings are implemented in
                 the deep web search engine Factal. We demonstrate that
                 the agreement analysis tracks source corruption.
                 Further, our relevance evaluations show that our
                 methods improve precision significantly over Google
                 Base and the other baseline methods. The result ranking
                 and the domain-specific source ranking are evaluated
                 separately.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "11",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Nguyen:2013:FWT,
  author =       "Cam-Tu Nguyen and Natsuda Kaothanthong and Takeshi
                 Tokuyama and Xuan-Hieu Phan",
  title =        "A feature-word-topic model for image annotation and
                 retrieval",
  journal =      j-TWEB,
  volume =       "7",
  number =       "3",
  pages =        "12:1--12:??",
  month =        sep,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2516633.2516634",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:20 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Image annotation is a process of finding appropriate
                 semantic labels for images in order to obtain a more
                 convenient way for indexing and searching images on the
                 Web. This article proposes a novel method for image
                 annotation based on combining feature-word
                 distributions, which map from visual space to word
                 space, and word-topic distributions, which form a
                 structure to capture label relationships for
                 annotation. We refer to this type of model as
                 Feature-Word-Topic models. The introduction of topics
                 allows us to efficiently take word associations, such
                 as {ocean, fish, coral} or {desert, sand, cactus}, into
                 account for image annotation. Unlike previous
                 topic-based methods, we do not consider topics as joint
                 distributions of words and visual features, but as
                 distributions of words only. Feature-word distributions
                 are utilized to define weights in computation of topic
                 distributions for annotation. By doing so, topic models
                 in text mining can be applied directly in our method.
                 Our Feature-word-topic model, which exploits Gaussian
                 Mixtures for feature-word distributions, and
                 probabilistic Latent Semantic Analysis (pLSA) for
                 word-topic distributions, shows that our method is able
                 to obtain promising results in image annotation and
                 retrieval.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "12",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Vargiu:2013:ICA,
  author =       "Eloisa Vargiu and Alessandro Giuliani and Giuliano
                 Armano",
  title =        "Improving contextual advertising by adopting
                 collaborative filtering",
  journal =      j-TWEB,
  volume =       "7",
  number =       "3",
  pages =        "13:1--13:??",
  month =        sep,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2516633.2516635",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:20 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Contextual advertising can be viewed as an information
                 filtering task aimed at selecting suitable ads to be
                 suggested to the final ``user'', that is, the Web page
                 in hand. Starting from this insight, in this article we
                 propose a novel system, which adopts a collaborative
                 filtering approach to perform contextual advertising.
                 In particular, given a Web page, the system relies on
                 collaborative filtering to classify the page content
                 and to suggest suitable ads accordingly. Useful
                 information is extracted from ``inlinks'', that is,
                 similar pages that link to the Web page in hand. In so
                 doing, collaborative filtering is used in a
                 content-based setting, giving rise to a hybrid
                 contextual advertising system. After being implemented,
                 the system has been experimented with about 15000 Web
                 pages extracted from the Open Directory Project.
                 Comparative experiments with a content-based system
                 have been performed. The corresponding results
                 highlight that the proposed system performs better. A
                 suitable case study is also provided to enable the
                 reader to better understand how the system works and
                 its effectiveness.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "13",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Conti:2013:VPS,
  author =       "Mauro Conti and Arbnor Hasani and Bruno Crispo",
  title =        "Virtual private social networks and a {Facebook}
                 implementation",
  journal =      j-TWEB,
  volume =       "7",
  number =       "3",
  pages =        "14:1--14:??",
  month =        sep,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2516633.2516636",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:20 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The popularity of Social Networking Sites (SNS) is
                 growing rapidly, with the largest sites serving
                 hundreds of millions of users and their private
                 information. The privacy settings of these SNSs do not
                 allow the user to avoid sharing some information (e.g.,
                 name and profile picture) with all the other users.
                 Also, no matter the privacy settings, this information
                 is always shared with the SNS (that could sell this
                 information or be hacked). To mitigate these threats,
                 we recently introduced the concept of Virtual Private
                 Social Networks (VPSNs). In this work we propose the
                 first complete architecture and implementation of VPSNs
                 for Facebook. In particular, we address an important
                 problem left unexplored in our previous research-that
                 is the automatic propagation of updated profiles to all
                 the members of the same VPSN. Furthermore, we made an
                 in-depth study on performance and implemented several
                 optimization to reduce the impact of VPSN on user
                 experience. The proposed solution is lightweight,
                 completely distributed, does not depend on the
                 collaboration from Facebook, does not have a central
                 point of failure, it offers (with some limitations) the
                 same functionality as Facebook, and apart from some
                 simple settings, the solution is almost transparent to
                 the user. Thorough experiments, with an extended set of
                 parameters, we have confirmed the feasibility of the
                 proposal and have shown a very limited time-overhead
                 experienced by the user while browsing Facebook
                 pages.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "14",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Cambazoglu:2013:TBI,
  author =       "B. Barla Cambazoglu and Enver Kayaaslan and Simon
                 Jonassen and Cevdet Aykanat",
  title =        "A term-based inverted index partitioning model for
                 efficient distributed query processing",
  journal =      j-TWEB,
  volume =       "7",
  number =       "3",
  pages =        "15:1--15:??",
  month =        sep,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2516633.2516637",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:20 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "In a shared-nothing, distributed text retrieval
                 system, queries are processed over an inverted index
                 that is partitioned among a number of index servers. In
                 practice, the index is either document-based or
                 term-based partitioned. This choice is made depending
                 on the properties of the underlying hardware
                 infrastructure, query traffic distribution, and some
                 performance and availability constraints. In query
                 processing on retrieval systems that adopt a term-based
                 index partitioning strategy, the high communication
                 overhead due to the transfer of large amounts of data
                 from the index servers forms a major performance
                 bottleneck, deteriorating the scalability of the entire
                 distributed retrieval system. In this work, to
                 alleviate this problem, we propose a novel inverted
                 index partitioning model that relies on hypergraph
                 partitioning. In the proposed model, concurrently
                 accessed index entries are assigned to the same index
                 servers, based on the inverted index access patterns
                 extracted from the past query logs. The model aims to
                 minimize the communication overhead that will be
                 incurred by future queries while maintaining the
                 computational load balance among the index servers. We
                 evaluate the performance of the proposed model through
                 extensive experiments using a real-life text collection
                 and a search query sample. Our results show that
                 considerable performance gains can be achieved relative
                 to the term-based index partitioning strategies
                 previously proposed in literature. In most cases,
                 however, the performance remains inferior to that
                 attained by document-based partitioning.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "15",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Weninger:2013:PPF,
  author =       "Tim Weninger and Thomas J. Johnston and Jiawei Han",
  title =        "The parallel path framework for entity discovery on
                 the web",
  journal =      j-TWEB,
  volume =       "7",
  number =       "3",
  pages =        "16:1--16:??",
  month =        sep,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2516633.2516638",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:20 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "It has been a dream of the database and Web
                 communities to reconcile the unstructured nature of the
                 World Wide Web with the neat, structured schemas of the
                 database paradigm. Even though databases are currently
                 used to generate Web content in some sites, the schemas
                 of these databases are rarely consistent across a
                 domain. This makes the comparison and aggregation of
                 information from different domains difficult. We aim to
                 make an important step towards resolving this disparity
                 by using the structural and relational information on
                 the Web to (1) extract Web lists, (2) find
                 entity-pages, (3) map entity-pages to a database, and
                 (4) extract attributes of the entities. Specifically,
                 given a Web site and an entity-page (e.g., university
                 department and faculty member home page) we seek to
                 find all of the entity-pages of the same type (e.g.,
                 all faculty members in the department), as well as
                 attributes of the specific entities (e.g., their phone
                 numbers, email addresses, office numbers). To do this,
                 we propose a Web structure mining method which grows
                 parallel paths through the Web graph and DOM trees and
                 propagates relevant attribute information forward. We
                 show that by utilizing these parallel paths we can
                 efficiently discover entity-pages and attributes.
                 Finally, we demonstrate the accuracy of our method with
                 a large case study.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "16",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Liu:2013:SCB,
  author =       "Liwei Liu and Freddy Lecue and Nikolay Mehandjiev",
  title =        "Semantic content-based recommendation of software
                 services using context",
  journal =      j-TWEB,
  volume =       "7",
  number =       "3",
  pages =        "17:1--17:??",
  month =        sep,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2516633.2516639",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:20 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The current proliferation of software services means
                 users should be supported when selecting one service
                 out of the many which meet their needs. Recommender
                 Systems provide such support for selecting products and
                 conventional services, yet their direct application to
                 software services is not straightforward, because of
                 the current scarcity of available user feedback, and
                 the need to fine-tune software services to the context
                 of intended use. In this article, we address these
                 issues by proposing a semantic content-based
                 recommendation approach that analyzes the context of
                 intended service use to provide effective
                 recommendations in conditions of scarce user feedback.
                 The article ends with two experiments based on a
                 realistic set of semantic services. The first
                 experiment demonstrates how the proposed semantic
                 content-based approach can produce effective
                 recommendations using semantic reasoning over service
                 specifications by comparing it with three other
                 approaches. The second experiment demonstrates the
                 effectiveness of the proposed context analysis
                 mechanism by comparing the performance of both
                 context-aware and plain versions of our semantic
                 content-based approach, benchmarked against
                 user-performed selection informed by context.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "17",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Jiang:2013:ULI,
  author =       "Jing Jiang and Christo Wilson and Xiao Wang and
                 Wenpeng Sha and Peng Huang and Yafei Dai and Ben Y.
                 Zhao",
  title =        "Understanding latent interactions in online social
                 networks",
  journal =      j-TWEB,
  volume =       "7",
  number =       "4",
  pages =        "18:1--18:??",
  month =        oct,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2517040",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:21 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Popular online social networks (OSNs) like Facebook
                 and Twitter are changing the way users communicate and
                 interact with the Internet. A deep understanding of
                 user interactions in OSNs can provide important
                 insights into questions of human social behavior and
                 into the design of social platforms and applications.
                 However, recent studies have shown that a majority of
                 user interactions on OSNs are latent interactions, that
                 is, passive actions, such as profile browsing, that
                 cannot be observed by traditional measurement
                 techniques. In this article, we seek a deeper
                 understanding of both active and latent user
                 interactions in OSNs. For quantifiable data on latent
                 user interactions, we perform a detailed measurement
                 study on Renren, the largest OSN in China with more
                 than 220 million users to date. All friendship links in
                 Renren are public, allowing us to exhaustively crawl a
                 connected graph component of 42 million users and 1.66
                 billion social links in 2009. Renren also keeps
                 detailed, publicly viewable visitor logs for each user
                 profile. We capture detailed histories of profile
                 visits over a period of 90 days for users in the Peking
                 University Renren network and use statistics of profile
                 visits to study issues of user profile popularity,
                 reciprocity of profile visits, and the impact of
                 content updates on user popularity. We find that latent
                 interactions are much more prevalent and frequent than
                 active events, are nonreciprocal in nature, and that
                 profile popularity is correlated with page views of
                 content rather than with quantity of content updates.
                 Finally, we construct latent interaction graphs as
                 models of user browsing behavior and compare their
                 structural properties, evolution, community structure,
                 and mixing times against those of both active
                 interaction graphs and social graphs.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "18",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Quarteroni:2013:BKA,
  author =       "Silvia Quarteroni and Marco Brambilla and Stefano
                 Ceri",
  title =        "A bottom-up, knowledge-aware approach to integrating
                 and querying {Web} data services",
  journal =      j-TWEB,
  volume =       "7",
  number =       "4",
  pages =        "19:1--19:??",
  month =        oct,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2493536",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:21 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "As a wealth of data services is becoming available on
                 the Web, building and querying Web applications that
                 effectively integrate their content is increasingly
                 important. However, schema integration and ontology
                 matching with the aim of registering data services
                 often requires a knowledge-intensive, tedious, and
                 error-prone manual process. We tackle this issue by
                 presenting a bottom-up, semi-automatic service
                 registration process that refers to an external
                 knowledge base and uses simple text processing
                 techniques in order to minimize and possibly avoid the
                 contribution of domain experts in the annotation of
                 data services. The first by-product of this process is
                 a representation of the domain of data services as an
                 entity-relationship diagram, whose entities are named
                 after concepts of the external knowledge base matching
                 service terminology rather than being manually created
                 to accommodate an application-specific ontology.
                 Second, a three-layer annotation of service semantics
                 (service interfaces, access patterns, service marts)
                 describing how services ``play'' with such domain
                 elements is also automatically constructed at
                 registration time. When evaluated against heterogeneous
                 existing data services and with a synthetic service
                 dataset constructed using Google Fusion Tables, the
                 approach yields good results in terms of data
                 representation accuracy. We subsequently demonstrate
                 that natural language processing methods can be used to
                 decompose and match simple queries to the data services
                 represented in three layers according to the preceding
                 methodology with satisfactory results. We show how
                 semantic annotations are used at query time to convert
                 the user's request into an executable logical query.
                 Globally, our findings show that the proposed
                 registration method is effective in creating a uniform
                 semantic representation of data services, suitable for
                 building Web applications and answering search
                 queries.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "19",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Leiva:2013:WBB,
  author =       "Luis A. Leiva and Roberto Viv{\'o}",
  title =        "{Web} browsing behavior analysis and interactive
                 hypervideo",
  journal =      j-TWEB,
  volume =       "7",
  number =       "4",
  pages =        "20:1--20:??",
  month =        oct,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2529995.2529996",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:21 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Processing data on any sort of user interaction is
                 well known to be cumbersome and mostly time consuming.
                 In order to assist researchers in easily inspecting
                 fine-grained browsing data, current tools usually
                 display user interactions as mouse cursor tracks, a
                 video-like visualization scheme. However, to date,
                 traditional online video inspection has not explored
                 the full capabilities of hypermedia and interactive
                 techniques. In response to this need, we have developed
                 SMT2 \epsilon , a Web-based tracking system for
                 analyzing browsing behavior using feature-rich
                 hypervideo visualizations. We compare our system to
                 related work in academia and the industry, showing that
                 ours features unprecedented visualization capabilities.
                 We also show that SMT2 \epsilon efficiently captures
                 browsing data and is perceived by users to be both
                 helpful and usable. A series of prediction experiments
                 illustrate that raw cursor data are accessible and can
                 be easily handled, providing evidence that the data can
                 be used to construct and verify research hypotheses.
                 Considering its limitations, it is our hope that SMT2
                 \epsilon will assist researchers, usability
                 practitioners, and other professionals interested in
                 understanding how users browse the Web.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "20",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Bing:2013:RDS,
  author =       "Lidong Bing and Wai Lam and Tak-Lam Wong",
  title =        "Robust detection of semi-structured web records using
                 a {DOM} structure-knowledge-driven model",
  journal =      j-TWEB,
  volume =       "7",
  number =       "4",
  pages =        "21:1--21:??",
  month =        oct,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2508434",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:21 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Web data record extraction aims at extracting a set of
                 similar object records from a single webpage. These
                 records have similar attributes or fields and are
                 presented with a regular format in a coherent region of
                 the page. To tackle this problem, most existing works
                 analyze the DOM tree of an input page. One major
                 limitation of these methods is that the lack of a
                 global view in detecting data records from an input
                 page results in a myopic decision. Their brute-force
                 searching manner in detecting various types of records
                 degrades the flexibility and robustness. We propose a
                 Structure-Knowledge-Oriented Global Analysis (Skoga)
                 framework which can perform robust detection of
                 different-kinds of data records and record regions. The
                 major component of the Skoga framework is a DOM
                 structure-knowledge-driven detection model which can
                 conduct a global analysis on the DOM structure to
                 achieve effective detection. The DOM structure
                 knowledge consists of background knowledge as well as
                 statistical knowledge capturing different
                 characteristics of data records and record regions, as
                 exhibited in the DOM structure. The background
                 knowledge encodes the semantics of labels indicating
                 general constituents of data records and regions. The
                 statistical knowledge is represented by some carefully
                 designed features that capture different
                 characteristics of a single node or a node group in the
                 DOM. The feature weights are determined using a
                 development dataset via a parameter estimation
                 algorithm based on a structured output support vector
                 machine. An optimization method based on the
                 divide-and-conquer principle is developed making use of
                 the DOM structure knowledge to quantitatively infer and
                 recognize appropriate records and regions for a page.
                 Extensive experiments have been conducted on four
                 datasets. The experimental results demonstrate that our
                 framework achieves higher accuracy compared with
                 state-of-the-art methods.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "21",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Liao:2013:VAC,
  author =       "Zhen Liao and Daxin Jiang and Jian Pei and Yalou Huang
                 and Enhong Chen and Huanhuan Cao and Hang Li",
  title =        "A {vlHMM} approach to context-aware search",
  journal =      j-TWEB,
  volume =       "7",
  number =       "4",
  pages =        "22:1--22:??",
  month =        oct,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2490255",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:21 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Capturing the context of a user's query from the
                 previous queries and clicks in the same session leads
                 to a better understanding of the user's information
                 need. A context-aware approach to document reranking,
                 URL recommendation, and query suggestion may
                 substantially improve users' search experience. In this
                 article, we propose a general approach to context-aware
                 search by learning a variable length hidden Markov
                 model ( vlHMM ) from search sessions extracted from log
                 data. While the mathematical model is powerful, the
                 huge amounts of log data present great challenges. We
                 develop several distributed learning techniques to
                 learn a very large vlHMM under the map-reduce
                 framework. Moreover, we construct feature vectors for
                 each state of the vlHMM model to handle users' novel
                 queries not covered by the training data. We test our
                 approach on a raw dataset consisting of 1.9 billion
                 queries, 2.9 billion clicks, and 1.2 billion search
                 sessions before filtering, and evaluate the
                 effectiveness of the vlHMM learned from the real data
                 on three search applications: document reranking, query
                 suggestion, and URL recommendation. The experiment
                 results validate the effectiveness of vlHMM in the
                 applications of document reranking, URL recommendation,
                 and query suggestion.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "22",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{White:2013:CBD,
  author =       "Ryen W. White and Eric Horvitz",
  title =        "Captions and biases in diagnostic search",
  journal =      j-TWEB,
  volume =       "7",
  number =       "4",
  pages =        "23:1--23:??",
  month =        oct,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2486040",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:21 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "People frequently turn to the Web with the goal of
                 diagnosing medical symptoms. Studies have shown that
                 diagnostic search can often lead to anxiety about the
                 possibility that symptoms are explained by the presence
                 of rare, serious medical disorders, rather than far
                 more common benign syndromes. We study the influence of
                 the appearance of potentially-alarming content, such as
                 severe illnesses or serious treatment options
                 associated with the queried for symptoms, in captions
                 comprising titles, snippets, and URLs. We explore
                 whether users are drawn to results with
                 potentially-alarming caption content, and if so, the
                 implications of such attraction for the design of
                 search engines. We specifically study the influence of
                 the content of search result captions shown in response
                 to symptom searches on search-result click-through
                 behavior. We show that users are significantly more
                 likely to examine and click on captions containing
                 potentially-alarming medical terminology such as
                 ``heart attack'' or ``medical emergency'' independent
                 of result rank position and well-known positional
                 biases in users' search examination behaviors. The
                 findings provide insights about the possible effects of
                 displaying implicit correlates of searchers' goals in
                 search-result captions, such as unexpressed concerns
                 and fears. As an illustration of the potential utility
                 of these results, we developed and evaluated an
                 enhanced click prediction model that incorporates
                 potentially-alarming caption features and show that it
                 significantly outperforms models that ignore caption
                 content. Beyond providing additional understanding of
                 the effects of Web content on medical concerns, the
                 methods and findings have implications for search
                 engine design. As part of our discussion on the
                 implications of this research, we propose procedures
                 for generating more representative captions that may be
                 less likely to cause alarm, as well as methods for
                 learning to more appropriately rank search results from
                 logged search behavior, for examples, by also
                 considering the presence of potentially-alarming
                 content in the captions that motivate observed clicks
                 and down-weighting clicks seemingly driven by
                 searchers' health anxieties.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "23",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Lee:2013:SCA,
  author =       "Jung-Hyun Lee and Jongwoo Ha and Jin-Yong Jung and
                 Sangkeun Lee",
  title =        "Semantic contextual advertising based on the open
                 directory project",
  journal =      j-TWEB,
  volume =       "7",
  number =       "4",
  pages =        "24:1--24:??",
  month =        oct,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2529995.2529997",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:21 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Contextual advertising seeks to place relevant textual
                 ads within the content of generic webpages. In this
                 article, we explore a novel semantic approach to
                 contextual advertising. This consists of three tasks:
                 (1) building a well-organized hierarchical taxonomy of
                 topics, (2) developing a robust classifier for
                 effectively finding the topics of pages and ads, and
                 (3) ranking ads based on the topical relevance to
                 pages. First, we heuristically build our own taxonomy
                 of topics from the Open Directory Project (ODP).
                 Second, we investigate how to increase classification
                 accuracy by taking the unique characteristics of the
                 ODP into account. Last, we measure the topical
                 relevance of ads by applying a link analysis technique
                 to the similarity graph carefully derived from our
                 taxonomy. Experiments show that our classification
                 method improves the performance of Ma- F$_1$ by as much
                 as 25.7\% over the baseline classifier. In addition,
                 our ranking method enhances the relevance of ads
                 substantially, up to 10\% in terms of precision at k,
                 compared to a representative strategy.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "24",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Huang:2013:UEQ,
  author =       "Xiaodi Huang",
  title =        "{UsageQoS}: Estimating the {QoS} of {Web} Services
                 through Online User Communities",
  journal =      j-TWEB,
  volume =       "8",
  number =       "1",
  pages =        "1:1--1:??",
  month =        dec,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2532635",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:23 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Services are an indispensable component in cloud
                 computing. Web services are particularly important. As
                 an increasing number of Web services provides
                 equivalent functions, one common issue faced by users
                 is the selection of the most appropriate one based on
                 quality. This article presents a conceptual framework
                 that characterizes the quality of Web services, an
                 algorithm that quantifies them, and a system
                 architecture that ranks Web services by using the
                 proposed algorithm. In particular, the algorithm,
                 called UsageQoS that computes the scores of quality of
                 service (QoS) of Web services within a community, makes
                 use of the usage frequencies of Web services. The
                 frequencies are defined as the numbers of times invoked
                 by other services in a given time period. The UsageQoS
                 algorithm is able to optionally take user ratings as
                 its initial input. The proposed approach has been
                 validated by extensively experimenting on several
                 datasets, including two real datasets. The results of
                 the experiments have demonstrated that our approach is
                 capable of estimating QoS parameters of Web services,
                 regardless of whether user ratings are available or
                 not.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "1",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Weber:2013:FBW,
  author =       "Ingo Weber and Hye-Young Paik and Boualem Benatallah",
  title =        "Form-Based {Web} Service Composition for Domain
                 Experts",
  journal =      j-TWEB,
  volume =       "8",
  number =       "1",
  pages =        "2:1--2:??",
  month =        dec,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2542168",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:23 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "In many cases, it is not cost effective to automate
                 business processes which affect a small number of
                 people and/or change frequently. We present a novel
                 approach for enabling domain experts to model and
                 deploy such processes from their respective domain as
                 Web service compositions. The approach builds on
                 user-editable service, naming and representing Web
                 services as forms. On this basis, the approach provides
                 a visual composition language with a targeted
                 restriction of control-flow expressivity, process
                 simulation, automated process verification mechanisms,
                 and code generation for executing orchestrations. A
                 Web-based service composition prototype implements this
                 approach, including a WS-BPEL code generator. A small
                 lab user study with 14 participants showed promising
                 results for the usability of the system, even for
                 nontechnical domain experts.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "2",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Ozcan:2013:SCH,
  author =       "Rifat Ozcan and Ismail Sengor Altingovde and B. Barla
                 Cambazoglu and {\"O}zg{\"u}r Ulusoy",
  title =        "Second Chance: a Hybrid Approach for Dynamic Result
                 Caching and Prefetching in Search Engines",
  journal =      j-TWEB,
  volume =       "8",
  number =       "1",
  pages =        "3:1--3:??",
  month =        dec,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2536777",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:23 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Web search engines are known to cache the results of
                 previously issued queries. The stored results typically
                 contain the document summaries and some data that is
                 used to construct the final search result page returned
                 to the user. An alternative strategy is to store in the
                 cache only the result document IDs, which take much
                 less space, allowing results of more queries to be
                 cached. These two strategies lead to an interesting
                 trade-off between the hit rate and the average query
                 response latency. In this work, in order to exploit
                 this trade-off, we propose a hybrid result caching
                 strategy where a dynamic result cache is split into two
                 sections: an HTML cache and a docID cache. Moreover,
                 using a realistic cost model, we evaluate the
                 performance of different result prefetching strategies
                 for the proposed hybrid cache and the baseline
                 HTML-only cache. Finally, we propose a machine learning
                 approach to predict singleton queries, which occur only
                 once in the query stream. We show that when the
                 proposed hybrid result caching strategy is coupled with
                 the singleton query predictor, the hit rate is further
                 improved.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "3",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Sherkat:2013:ETS,
  author =       "Reza Sherkat and Jing Li and Nikos Mamoulis",
  title =        "Efficient Time-Stamped Event Sequence Anonymization",
  journal =      j-TWEB,
  volume =       "8",
  number =       "1",
  pages =        "4:1--4:??",
  month =        dec,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2532643",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:23 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "With the rapid growth of applications which generate
                 timestamped sequences (click streams, GPS trajectories,
                 RFID sequences), sequence anonymization has become an
                 important problem, in that should such data be
                 published or shared. Existing trajectory anonymization
                 techniques disregard the importance of time or the
                 sensitivity of events. This article is the first, to
                 our knowledge, thorough study on time-stamped event
                 sequence anonymization. We propose a novel and tunable
                 generalization framework tailored to event sequences.
                 We generalize time stamps using time intervals and
                 events using a taxonomy which models the domain
                 semantics. We consider two scenarios: (i) sharing the
                 data with a single receiver (the SSR setting), where
                 the receiver's background knowledge is confined to a
                 set of time stamps and time generalization suffices,
                 and (ii) sharing the data with colluding receivers (the
                 SCR setting), where time generalization should be
                 combined with event generalization. For both cases, we
                 propose appropriate anonymization methods that prevent
                 both user identification and event prediction. To
                 achieve computational efficiency and scalability, we
                 propose optimization techniques for both cases using a
                 utility-based index, compact summaries, fast to compute
                 bounds for utility, and a novel taxonomy-aware distance
                 function. Extensive experiments confirm the
                 effectiveness of our approach compared with state of
                 the art, in terms of information loss, range query
                 distortion, and preserving temporal causality patterns.
                 Furthermore, our experiments demonstrate efficiency and
                 scalability on large-scale real and synthetic
                 datasets.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "4",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Bellido:2013:CFP,
  author =       "Jesus Bellido and Rosa Alarc{\'o}n and Cesare
                 Pautasso",
  title =        "Control-Flow Patterns for Decentralized {RESTful}
                 Service Composition",
  journal =      j-TWEB,
  volume =       "8",
  number =       "1",
  pages =        "5:1--5:??",
  month =        dec,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2535911",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:23 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The REST architectural style has attracted a lot of
                 interest from industry due to the nonfunctional
                 properties it contributes to Web-based solutions.
                 SOAP/WSDL-based services, on the other hand, provide
                 tools and methodologies that allow the design and
                 development of software supporting complex service
                 arrangements, enabling complex business processes which
                 make use of well-known control-flow patterns. It is not
                 clear if and how such patterns should be modeled,
                 considering RESTful Web services that comply with the
                 statelessness, uniform interface and hypermedia
                 constraints. In this article, we analyze a set of
                 fundamental control-flow patterns in the context of
                 stateless compositions of RESTful services. We propose
                 a means of enabling their implementation using the HTTP
                 protocol and discuss the impact of our design choices
                 according to key REST architectural principles. We hope
                 to shed new light on the design of basic building
                 blocks for RESTful business processes.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "5",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Chelaru:2013:ADE,
  author =       "Sergiu Chelaru and Ismail Sengor Altingovde and Stefan
                 Siersdorfer and Wolfgang Nejdl",
  title =        "Analyzing, Detecting, and Exploiting Sentiment in
                 {Web} Queries",
  journal =      j-TWEB,
  volume =       "8",
  number =       "1",
  pages =        "6:1--6:??",
  month =        dec,
  year =         "2013",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2535525",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Mar 13 08:28:23 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The Web contains an increasing amount of biased and
                 opinionated documents on politics, products, and
                 polarizing events. In this article, we present an
                 indepth analysis of Web search queries for
                 controversial topics, focusing on query sentiment. To
                 this end, we conduct extensive user assessments and
                 discriminative term analyses, as well as a sentiment
                 analysis using the SentiWordNet thesaurus, a lexical
                 resource containing sentiment annotations. Furthermore,
                 in order to detect the sentiment expressed in queries,
                 we build different classifiers based on query texts,
                 query result titles, and snippets. We demonstrate the
                 virtue of query sentiment detection in two different
                 use cases. First, we define a query recommendation
                 scenario that employs sentiment detection of results to
                 recommend additional queries for polarized queries
                 issued by search engine users. The second application
                 scenario is controversial topic discovery, where query
                 sentiment classifiers are employed to discover
                 previously unknown topics that trigger both highly
                 positive and negative opinions among the users of a
                 search engine. For both use cases, the results of our
                 evaluations on real-world data are promising and show
                 the viability and potential of query sentiment analysis
                 in practical scenarios.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "6",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Torres:2014:ASB,
  author =       "Sergio Duarte Torres and Ingmar Weber and Djoerd
                 Hiemstra",
  title =        "Analysis of Search and Browsing Behavior of Young
                 Users on the {Web}",
  journal =      j-TWEB,
  volume =       "8",
  number =       "2",
  pages =        "7:1--7:??",
  month =        mar,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2555595",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Apr 1 05:42:19 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The Internet is increasingly used by young children
                 for all kinds of purposes. Nonetheless, there are not
                 many resources especially designed for children on the
                 Internet and most of the content online is designed for
                 grown-up users. This situation is problematic if we
                 consider the large differences between young users and
                 adults since their topic interests, computer skills,
                 and language capabilities evolve rapidly during
                 childhood. There is little research aimed at exploring
                 and measuring the difficulties that children encounter
                 on the Internet when searching for information and
                 browsing for content. In the first part of this work,
                 we employed query logs from a commercial search engine
                 to quantify the difficulties children of different ages
                 encounter on the Internet and to characterize the
                 topics that they search for. We employed query metrics
                 (e.g., the fraction of queries posed in natural
                 language), session metrics (e.g., the fraction of
                 abandoned sessions), and click activity (e.g., the
                 fraction of ad clicks). The search logs were also used
                 to retrace stages of child development. Concretely, we
                 looked for changes in interests (e.g., the distribution
                 of topics searched) and language development (e.g., the
                 readability of the content accessed and the vocabulary
                 size). In the second part of this work, we employed
                 toolbar logs from a commercial search engine to
                 characterize the browsing behavior of young users,
                 particularly to understand the activities on the
                 Internet that trigger search. We quantified the
                 proportion of browsing and search activity in the
                 toolbar sessions and we estimated the likelihood of a
                 user to carry out search on the Web vertical and
                 multimedia verticals (i.e., videos and images) given
                 that the previous event is another search event or a
                 browsing event. We observed that these metrics clearly
                 demonstrate an increased level of confusion and
                 unsuccessful search sessions among children. We also
                 found a clear relation between the reading level of the
                 clicked pages and characteristics of the users such as
                 age and educational attainment. In terms of browsing
                 behavior, children were found to start their activities
                 on the Internet with a search engine (instead of
                 directly browsing content) more often than adults. We
                 also observed a significantly larger amount of browsing
                 activity for the case of teenager users. Interestingly
                 we also found that if children visit knowledge-related
                 Web sites (i.e., information-dense pages such as
                 Wikipedia articles), they subsequently do more Web
                 searches than adults. Additionally, children and
                 especially teenagers were found to have a greater
                 tendency to engage in multimedia search, which calls to
                 improve the aggregation of multimedia results into the
                 current search result pages.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "7",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Su:2014:HIY,
  author =       "Ao-Jan Su and Y. Charlie Hu and Aleksandar Kuzmanovic
                 and Cheng-Kok Koh",
  title =        "How to Improve Your Search Engine Ranking: Myths and
                 Reality",
  journal =      j-TWEB,
  volume =       "8",
  number =       "2",
  pages =        "8:1--8:??",
  month =        mar,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2579990",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Apr 1 05:42:19 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Search engines have greatly influenced the way people
                 access information on the Internet, as such engines
                 provide the preferred entry point to billions of pages
                 on the Web. Therefore, highly ranked Web pages
                 generally have higher visibility to people and pushing
                 the ranking higher has become the top priority for Web
                 masters. As a matter of fact, Search Engine
                 Optimization (SEO) has became a sizeable business that
                 attempts to improve their clients' ranking. Still, the
                 lack of ways to validate SEO's methods has created
                 numerous myths and fallacies associated with ranking
                 algorithms. In this article, we focus on two ranking
                 algorithms, Google's and Bing's, and design, implement,
                 and evaluate a ranking system to systematically
                 validate assumptions others have made about these
                 popular ranking algorithms. We demonstrate that linear
                 learning models, coupled with a recursive partitioning
                 ranking scheme, are capable of predicting ranking
                 results with high accuracy. As an example, we manage to
                 correctly predict 7 out of the top 10 pages for 78\% of
                 evaluated keywords. Moreover, for content-only ranking,
                 our system can correctly predict 9 or more pages out of
                 the top 10 ones for 77\% of search terms. We show how
                 our ranking system can be used to reveal the relative
                 importance of ranking features in a search engine's
                 ranking function, provide guidelines for SEOs and Web
                 masters to optimize their Web pages, validate or
                 disprove new ranking features, and evaluate search
                 engine ranking results for possible ranking bias.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "8",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Sirivianos:2014:LSF,
  author =       "Michael Sirivianos and Kyungbaek Kim and Jian Wei Gan
                 and Xiaowei Yang",
  title =        "Leveraging Social Feedback to Verify Online Identity
                 Claims",
  journal =      j-TWEB,
  volume =       "8",
  number =       "2",
  pages =        "9:1--9:??",
  month =        mar,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2543711",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Apr 1 05:42:19 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Anonymity is one of the main virtues of the Internet,
                 as it protects privacy and enables users to express
                 opinions more freely. However, anonymity hinders the
                 assessment of the veracity of assertions that online
                 users make about their identity attributes, such as age
                 or profession. We propose FaceTrust, a system that uses
                 online social networks to provide lightweight identity
                 credentials while preserving a user's anonymity.
                 FaceTrust employs a ``game with a purpose'' design to
                 elicit the opinions of the friends of a user about the
                 user's self-claimed identity attributes, and uses
                 attack-resistant trust inference to assign veracity
                 scores to identity attribute assertions. FaceTrust
                 provides credentials, which a user can use to
                 corroborate his assertions. We evaluate our proposal
                 using a live Facebook deployment and simulations on a
                 crawled social graph. The results show that our
                 veracity scores are strongly correlated with the ground
                 truth, even when dishonest users make up a large
                 fraction of the social network and employ the Sybil
                 attack.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "9",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Pugliese:2014:EMM,
  author =       "Andrea Pugliese and Matthias Br{\"o}cheler and V. S.
                 Subrahmanian and Michael Ovelg{\"o}nne",
  title =        "Efficient {MultiView} Maintenance under Insertion in
                 Huge Social Networks",
  journal =      j-TWEB,
  volume =       "8",
  number =       "2",
  pages =        "10:1--10:??",
  month =        mar,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2541290",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Apr 1 05:42:19 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Applications to monitor various aspects of social
                 networks are becoming increasingly popular. For
                 instance, marketers want to look for semantic patterns
                 relating to the content of tweets and Facebook posts
                 relating to their products. Law enforcement agencies
                 want to track behaviors involving potential criminals
                 on the Internet by looking for certain patterns of
                 behavior. Music companies want to track patterns of
                 spread of illegal music. These applications allow
                 multiple users to specify patterns of interest and
                 monitor them in real time as new data gets added to the
                 Web or to a social network. In this article we develop
                 the concept of social network view servers in which all
                 of these types of applications can be simultaneously
                 monitored. The patterns of interest are expressed as
                 views over an underlying graph or social network
                 database. We show that a given set of views can be
                 compiled in multiple possible ways to take advantage of
                 common substructures and define the concept of an
                 optimal merge. Though finding an optimal merge is shown
                 to be NP-hard, we develop the AddView to find very good
                 merges quickly. We develop a very fast MultiView
                 algorithm that scalably and efficiently maintains
                 multiple subgraph views when insertions are made to the
                 social network database. We show that our algorithm is
                 correct, study its complexity, and experimentally
                 demonstrate that our algorithm can scalably handle
                 updates to hundreds of views on 6 real-world social
                 network databases with up to 540M edges.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "10",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Bislimovska:2014:TCB,
  author =       "Bojana Bislimovska and Alessandro Bozzon and Marco
                 Brambilla and Piero Fraternali",
  title =        "Textual and Content-Based Search in Repositories of
                 {Web} Application Models",
  journal =      j-TWEB,
  volume =       "8",
  number =       "2",
  pages =        "11:1--11:??",
  month =        mar,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2579991",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Apr 1 05:42:19 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Model-driven engineering relies on collections of
                 models, which are the primary artifacts for software
                 development. To enable knowledge sharing and reuse,
                 models need to be managed within repositories, where
                 they can be retrieved upon users' queries. This article
                 examines two different techniques for indexing and
                 searching model repositories, with a focus on Web
                 development projects encoded in a domain-specific
                 language. Keyword-based and content-based search (also
                 known as query-by-example) are contrasted with respect
                 to the architecture of the system, the processing of
                 models and queries, and the way in which metamodel
                 knowledge can be exploited to improve search. A
                 thorough experimental evaluation is conducted to
                 examine what parameter configurations lead to better
                 accuracy and to offer an insight in what queries are
                 addressed best by each system.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "11",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Bellogin:2014:NSW,
  author =       "Alejandro Bellog{\'\i}n and Pablo Castells and
                 Iv{\'a}n Cantador",
  title =        "Neighbor Selection and Weighting in User-Based
                 Collaborative Filtering: a Performance Prediction
                 Approach",
  journal =      j-TWEB,
  volume =       "8",
  number =       "2",
  pages =        "12:1--12:??",
  month =        mar,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2579993",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Apr 1 05:42:19 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "User-based collaborative filtering systems suggest
                 interesting items to a user relying on similar-minded
                 people called neighbors. The selection and weighting of
                 these neighbors characterize the different
                 recommendation approaches. While standard strategies
                 perform a neighbor selection based on user
                 similarities, trust-aware recommendation algorithms
                 rely on other aspects indicative of user trust and
                 reliability. In this article we restate the trust-aware
                 recommendation problem, generalizing it in terms of
                 performance prediction techniques, whose goal is to
                 predict the performance of an information retrieval
                 system in response to a particular query. We
                 investigate how to adopt the preceding generalization
                 to define a unified framework where we conduct an
                 objective analysis of the effectiveness (predictive
                 power) of neighbor scoring functions. The proposed
                 framework enables discriminating whether recommendation
                 performance improvements are caused by the used
                 neighbor scoring functions or by the ways these
                 functions are used in the recommendation computation.
                 We evaluated our approach with several state-of-the-art
                 and novel neighbor scoring functions on three publicly
                 available datasets. By empirically comparing four
                 neighbor quality metrics and thirteen performance
                 predictors, we found strong predictive power for some
                 of the predictors with respect to certain metrics. This
                 result was then validated by checking the final
                 performance of recommendation strategies where
                 predictors are used for selecting and/or weighting user
                 neighbors. As a result, we have found that, by
                 measuring the predictive power of neighbor performance
                 predictors, we are able to anticipate which predictors
                 are going to perform better in neighbor-scoring-powered
                 versions of a user-based collaborative filtering
                 algorithm.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "12",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Qian:2014:FTD,
  author =       "Yi Qian and Sibel Adali",
  title =        "Foundations of Trust and Distrust in Networks:
                 Extended Structural Balance Theory",
  journal =      j-TWEB,
  volume =       "8",
  number =       "3",
  pages =        "13:1--13:??",
  month =        jun,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2628438",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed Jul 2 18:17:48 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Modeling trust in very large social networks is a hard
                 problem due to the highly noisy nature of these
                 networks that span trust relationships from many
                 different contexts, based on judgments of reliability,
                 dependability, and competence. Furthermore,
                 relationships in these networks vary in their level of
                 strength. In this article, we introduce a novel
                 extension of structural balance theory as a
                 foundational theory of trust and distrust in networks.
                 Our theory preserves the distinctions between trust and
                 distrust as suggested in the literature, but also
                 incorporates the notion of relationship strength that
                 can be expressed as either discrete categorical values,
                 as pairwise comparisons, or as metric distances. Our
                 model is novel, has sound social and psychological
                 basis, and captures the classical balance theory as a
                 special case. We then propose a convergence model,
                 describing how an imbalanced network evolves towards
                 new balance, and formulate the convergence problem of a
                 social network as a Metric Multidimensional Scaling
                 (MDS) optimization problem. Finally, we show how the
                 convergence model can be used to predict edge signs in
                 social networks and justify our theory through
                 extensive experiments on real datasets.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "13",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Soi:2014:CDC,
  author =       "Stefano Soi and Florian Daniel and Fabio Casati",
  title =        "Conceptual Development of Custom, Domain-Specific
                 Mashup Platforms",
  journal =      j-TWEB,
  volume =       "8",
  number =       "3",
  pages =        "14:1--14:??",
  month =        jun,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2628439",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed Jul 2 18:17:48 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Despite the common claim by mashup platforms that they
                 enable end-users to develop their own software, in
                 practice end-users still don't develop their own
                 mashups, as the highly technical or inexistent [sic]
                 user bases of today's mashup platforms testify. The key
                 shortcoming of current platforms is their
                 general-purpose nature, that privileges expressive
                 power over intuitiveness. In our prior work, we have
                 demonstrated that a domain-specific mashup approach,
                 which privileges intuitiveness over expressive power,
                 has much more potential to enable end-user development
                 (EUD). The problem is that developing mashup
                 platforms-domain-specific or not-is complex and time
                 consuming. In addition, domain-specific mashup
                 platforms by their very nature target only a small user
                 basis, that is, the experts of the target domain, which
                 makes their development not sustainable if it is not
                 adequately supported and automated. With this article,
                 we aim to make the development of custom,
                 domain-specific mashup platforms cost-effective. We
                 describe a mashup tool development kit (MDK) that is
                 able to automatically generate a mashup platform
                 (comprising custom mashup and component description
                 languages and design-time and runtime environments)
                 from a conceptual design and to provision it as a
                 service. We equip the kit with a dedicated development
                 methodology and demonstrate the applicability and
                 viability of the approach with the help of two case
                 studies.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "14",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Zhang:2014:PBT,
  author =       "Xianchao Zhang and You Wang and Nan Mou and Wenxin
                 Liang",
  title =        "Propagating Both Trust and Distrust with Target
                 Differentiation for Combating Link-Based {Web} Spam",
  journal =      j-TWEB,
  volume =       "8",
  number =       "3",
  pages =        "15:1--15:??",
  month =        jun,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2628440",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed Jul 2 18:17:48 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Semi-automatic anti-spam algorithms propagate either
                 trust through links from a good seed set (e.g.,
                 TrustRank) or distrust through inverse links from a bad
                 seed set (e.g., Anti-TrustRank) to the entire Web.
                 These kinds of algorithms have shown their powers in
                 combating link-based Web spam since they integrate both
                 human judgement and machine intelligence. Nevertheless,
                 there is still much space for improvement. One issue of
                 most existing trust/distrust propagation algorithms is
                 that only trust or distrust is propagated and only a
                 good seed set or a bad seed set is used. According to
                 Wu et al. [2006a], a combined usage of both trust and
                 distrust propagation can lead to better results, and an
                 effective framework is needed to realize this insight.
                 Another more serious issue of existing algorithms is
                 that trust or distrust is propagated in nondifferential
                 ways, that is, a page propagates its trust or distrust
                 score uniformly to its neighbors, without considering
                 whether each neighbor should be trusted or distrusted.
                 Such kinds of blind propagating schemes are
                 inconsistent with the original intention of
                 trust/distrust propagation. However, it seems
                 impossible to implement differential propagation if
                 only trust or distrust is propagated. In this article,
                 we take the view that each Web page has both a
                 trustworthy side and an untrustworthy side, and we
                 thusly assign two scores to each Web page: T-Rank,
                 scoring the trustworthiness of the page, and D-Rank,
                 scoring the untrustworthiness of the page. We then
                 propose an integrated framework that propagates both
                 trust and distrust. In the framework, the propagation
                 of T-Rank/D-Rank is penalized by the target's current
                 D-Rank/T-Rank. In other words, the propagation of
                 T-Rank/D-Rank is decided by the target's current
                 (generalized) probability of being
                 trustworthy/untrustworthy; thus a page propagates more
                 trust/distrust to a trustworthy/untrustworthy neighbor
                 than to an untrustworthy/trustworthy neighbor. In this
                 way, propagating both trust and distrust with target
                 differentiation is implemented. We use T-Rank scores to
                 realize spam demotion and D-Rank scores to accomplish
                 spam detection. The proposed Trust-DistrustRank (TDR)
                 algorithm regresses to TrustRank and Anti-TrustRank
                 when the penalty factor is set to 1 and 0,
                 respectively. Thus TDR could be seen as a combinatorial
                 generalization of both TrustRank and Anti-TrustRank.
                 TDR not only makes full use of both trust and distrust
                 propagation, but also overcomes the disadvantages of
                 both TrustRank and Anti-TrustRank. Experimental results
                 on benchmark datasets show that TDR outperforms other
                 semi-automatic anti-spam algorithms for both spam
                 demotion and spam detection tasks under various
                 criteria.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "15",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Margaritis:2014:ITI,
  author =       "Giorgos Margaritis and Stergios V. Anastasiadis",
  title =        "Incremental Text Indexing for Fast Disk-Based Search",
  journal =      j-TWEB,
  volume =       "8",
  number =       "3",
  pages =        "16:1--16:??",
  month =        jun,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2560800",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed Jul 2 18:17:48 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Real-time search requires to incrementally ingest
                 content updates and almost immediately make them
                 searchable while serving search queries at low latency.
                 This is currently feasible for datasets of moderate
                 size by fully maintaining the index in the main memory
                 of multiple machines. Instead, disk-based methods for
                 incremental index maintenance substantially increase
                 search latency with the index fragmented across
                 multiple disk locations. For the support of fast search
                 over disk-based storage, we take a fresh look at
                 incremental text indexing in the context of current
                 architectural features. We introduce a greedy method
                 called Selective Range Flush (SRF) to contiguously
                 organize the index over disk blocks and dynamically
                 update it at low cost. We show that SRF requires
                 substantial experimental effort to tune specific
                 parameters for performance efficiency. Subsequently, we
                 propose the Unified Range Flush (URF) method, which is
                 conceptually simpler than SRF, achieves similar or
                 better performance with fewer parameters and less
                 tuning, and is amenable to I/O complexity analysis. We
                 implement interesting variations of the two methods in
                 the Proteus prototype search engine that we developed
                 and do extensive experiments with three different Web
                 datasets of size up to 1TB. Across different systems,
                 we show that our methods offer search latency that
                 matches or reduces up to half the lowest achieved by
                 existing disk-based methods. In comparison to an
                 existing method of comparable search latency on the
                 same system, our methods reduce by a factor of 2.0--2.4
                 the I/O part of build time and by 21--24\% the total
                 build time.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "16",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Siersdorfer:2014:AMC,
  author =       "Stefan Siersdorfer and Sergiu Chelaru and Jose {San
                 Pedro} and Ismail Sengor Altingovde and Wolfgang
                 Nejdl",
  title =        "Analyzing and Mining Comments and Comment Ratings on
                 the Social {Web}",
  journal =      j-TWEB,
  volume =       "8",
  number =       "3",
  pages =        "17:1--17:??",
  month =        jun,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2628441",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed Jul 2 18:17:48 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "An analysis of the social video sharing platform
                 YouTube and the news aggregator Yahoo! News reveals the
                 presence of vast amounts of community feedback through
                 comments for published videos and news stories, as well
                 as through metaratings for these comments. This article
                 presents an in-depth study of commenting and comment
                 rating behavior on a sample of more than 10 million
                 user comments on YouTube and Yahoo! News. In this
                 study, comment ratings are considered first-class
                 citizens. Their dependencies with textual content,
                 thread structure of comments, and associated content
                 (e.g., videos and their metadata) are analyzed to
                 obtain a comprehensive understanding of the community
                 commenting behavior. Furthermore, this article explores
                 the applicability of machine learning and data mining
                 to detect acceptance of comments by the community,
                 comments likely to trigger discussions, controversial
                 and polarizing content, and users exhibiting offensive
                 commenting behavior. Results from this study have
                 potential application in guiding the design of
                 community-oriented online discussion platforms.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "17",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Casteleyn:2014:TYR,
  author =       "Sven Casteleyn and Irene Garrig{\'o}s and
                 Jose-Norberto Maz{\'o}n",
  title =        "Ten Years of {Rich Internet Applications}: a
                 Systematic Mapping Study, and Beyond",
  journal =      j-TWEB,
  volume =       "8",
  number =       "3",
  pages =        "18:1--18:??",
  month =        jun,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2626369",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed Jul 2 18:17:48 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The term Rich Internet Applications (RIAs) is
                 generally associated with Web applications that provide
                 the features and functionality of traditional desktop
                 applications. Ten years after the introduction of the
                 term, an ample amount of research has been carried out
                 to study various aspects of RIAs. It has thus become
                 essential to summarize this research and provide an
                 adequate overview. OBJECTIVE. The objective of our
                 study is to assemble, classify, and analyze all RIA
                 research performed in the scientific community, thus
                 providing a consolidated overview thereof, and to
                 identify well-established topics, trends, and open
                 research issues. Additionally, we provide a qualitative
                 discussion of the most interesting findings. This work
                 therefore serves as a reference work for beginning and
                 established RIA researchers alike, as well as for
                 industrial actors that need an introduction in the
                 field, or seek pointers to (a specific subset of) the
                 state-of-the-art. METHOD. A systematic mapping study is
                 performed in order to identify all RIA-related
                 publications, define a classification scheme, and
                 categorize, analyze, and discuss the identified
                 research according to it. RESULTS. Our source
                 identification phase resulted in 133 relevant,
                 peer-reviewed publications, published between 2002 and
                 2011 in a wide variety of venues. They were
                 subsequently classified according to four facets:
                 development activity, research topic, contribution
                 type, and research type. Pie, stacked bar, and bubble
                 charts were used to depict and analyze the results. A
                 deeper analysis is provided for the most interesting
                 and/or remarkable results. CONCLUSION. Analysis of the
                 results shows that, although the RIA term was coined in
                 2002, the first RIA-related research appeared in 2004.
                 From 2007 there was a significant increase in research
                 activity, peaking in 2009 and decreasing to pre-2009
                 levels afterwards. All development phases are covered
                 in the identified research, with emphasis on ``design''
                 (33\%) and ``implementation'' (29\%). The majority of
                 research proposes a ``method'' (44\%), followed by
                 ``model'' (22\%), ``methodology'' (18\%), and ``tools''
                 (16\%); no publications in the category ``metrics''
                 were found. The preponderant research topic is
                 ``models, methods and methodologies'' (23\%) and, to a
                 lesser extent, ``usability and accessibility'' and
                 ``user interface'' (11\% each). On the other hand, the
                 topic ``localization, internationalization and
                 multilinguality'' received no attention at all, and
                 topics such as ``deep Web'' (under 1\%), ``business
                 processing'', ``usage analysis'', ``data management'',
                 ``quality and metrics'' (all under 2\%), ``semantics'',
                 and ``performance'' (slightly above 2\%) received very
                 little attention. Finally, there is a large majority of
                 ``solution proposals'' (66\%), few ``evaluation
                 research'' (14\%), and even fewer ``validation'' (6\%),
                 although the latter have been increasing in recent
                 years.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "18",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Dincturk:2014:MBA,
  author =       "Mustafa Emre Dincturk and Guy-Vincent Jourdan and
                 Gregor V. Bochmann and Iosif Viorel Onut",
  title =        "A Model-Based Approach for Crawling {Rich Internet
                 Applications}",
  journal =      j-TWEB,
  volume =       "8",
  number =       "3",
  pages =        "19:1--19:??",
  month =        jun,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2626371",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed Jul 2 18:17:48 MDT 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "New Web technologies, like AJAX, result in more
                 responsive and interactive Web applications, sometimes
                 called Rich Internet Applications (RIAs). Crawling
                 techniques developed for traditional Web applications
                 are not sufficient for crawling RIAs. The inability to
                 crawl RIAs is a problem that needs to be addressed for
                 at least making RIAs searchable and testable. We
                 present a new methodology, called ``model-based
                 crawling'', that can be used as a basis to design
                 efficient crawling strategies for RIAs. We illustrate
                 model-based crawling with a sample strategy, called the
                 ``hypercube strategy''. The performances of our
                 model-based crawling strategies are compared against
                 existing standard crawling strategies, including
                 breadth-first, depth-first, and a greedy strategy.
                 Experimental results show that our model-based crawling
                 approach is significantly more efficient than these
                 standard strategies.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "19",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Dragut:2014:MQR,
  author =       "Eduard C. Dragut and Bhaskar Dasgupta and Brian P.
                 Beirne and Ali Neyestani and Badr Atassi and Clement Yu
                 and Weiyi Meng",
  title =        "Merging Query Results From Local Search Engines for
                 Georeferenced Objects",
  journal =      j-TWEB,
  volume =       "8",
  number =       "4",
  pages =        "20:1--20:??",
  month =        oct,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2656344",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Nov 6 16:08:07 MST 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The emergence of numerous online sources about local
                 services presents a need for more automatic yet
                 accurate data integration techniques. Local services
                 are georeferenced objects and can be queried by their
                 locations on a map, for instance, neighborhoods.
                 Typical local service queries (e.g., ``French
                 Restaurant in The Loop'') include not only information
                 about ``what'' (``French Restaurant'') a user is
                 searching for (such as cuisine) but also ``where''
                 information, such as neighborhood (``The Loop''). In
                 this article, we address three key problems: query
                 translation, result merging and ranking. Most local
                 search engines provide a (hierarchical) organization of
                 (large) cities into neighborhoods. A neighborhood in
                 one local search engine may correspond to sets of
                 neighborhoods in other local search engines. These make
                 the query translation challenging. To provide an
                 integrated access to the query results returned by the
                 local search engines, we need to combine the results
                 into a single list of results. Our contributions
                 include: (1) An integration algorithm for
                 neighborhoods. (2) A very effective business listing
                 resolution algorithm. (3) A ranking algorithm that
                 takes into consideration the user criteria, user
                 ratings and rankings. We have created a prototype
                 system, Yumi, over local search engines in the
                 restaurant domain. The restaurant domain is a
                 representative case study for the local services. We
                 conducted a comprehensive experimental study to
                 evaluate Yumi. A prototype version of Yumi is available
                 online.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "20",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Chen:2014:CCU,
  author =       "Xihui Chen and Jun Pang and Ran Xue",
  title =        "Constructing and Comparing User Mobility Profiles",
  journal =      j-TWEB,
  volume =       "8",
  number =       "4",
  pages =        "21:1--21:??",
  month =        oct,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2637483",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Nov 6 16:08:07 MST 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Nowadays, the accumulation of people's whereabouts due
                 to location-based applications has made it possible to
                 construct their mobility profiles. This access to
                 users' mobility profiles subsequently brings benefits
                 back to location-based applications. For instance, in
                 on-line social networks, friends can be recommended not
                 only based on the similarity between their registered
                 information, for instance, hobbies and professions but
                 also referring to the similarity between their mobility
                 profiles. In this article, we propose a new approach to
                 construct and compare users' mobility profiles. First,
                 we improve and apply frequent sequential pattern mining
                 technologies to extract the sequences of places that a
                 user frequently visits and use them to model his
                 mobility profile. Second, we present a new method to
                 calculate the similarity between two users using their
                 mobility profiles. More specifically, we identify the
                 weaknesses of a similarity metric in the literature,
                 and propose a new one which not only fixes the
                 weaknesses but also provides more precise and effective
                 similarity estimation. Third, we consider the semantics
                 of spatio-temporal information contained in user
                 mobility profiles and add them into the calculation of
                 user similarity. It enables us to measure users'
                 similarity from different perspectives. Two specific
                 types of semantics are explored in this article:
                 location semantics and temporal semantics. Last, we
                 validate our approach by applying it to two real-life
                 datasets collected by Microsoft Research Asia and
                 Yonsei University, respectively. The results show that
                 our approach outperforms the existing works from
                 several aspects.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "21",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Vural:2014:SFW,
  author =       "A. Gural Vural and B. Barla Cambazoglu and Pinar
                 Karagoz",
  title =        "Sentiment-Focused {Web} Crawling",
  journal =      j-TWEB,
  volume =       "8",
  number =       "4",
  pages =        "22:1--22:??",
  month =        oct,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2644821",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Nov 6 16:08:07 MST 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Sentiments and opinions expressed in Web pages towards
                 objects, entities, and products constitute an important
                 portion of the textual content available in the Web. In
                 the last decade, the analysis of such content has
                 gained importance due to its high potential for
                 monetization. Despite the vast interest in sentiment
                 analysis, somewhat surprisingly, the discovery of
                 sentimental or opinionated Web content is mostly
                 ignored. This work aims to fill this gap and addresses
                 the problem of quickly discovering and fetching the
                 sentimental content present in the Web. To this end, we
                 design a sentiment-focused Web crawling framework. In
                 particular, we propose different sentiment-focused Web
                 crawling strategies that prioritize discovered URLs
                 based on their predicted sentiment scores. Through
                 simulations, these strategies are shown to achieve
                 considerable performance improvement over
                 general-purpose Web crawling strategies in discovery of
                 sentimental Web content.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "22",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Kyusakov:2014:EFE,
  author =       "Rumen Kyusakov and Pablo Pu{\~n}al Pereira and Jens
                 Eliasson and Jerker Delsing",
  title =        "{EXIP}: a Framework for Embedded {Web} Development",
  journal =      j-TWEB,
  volume =       "8",
  number =       "4",
  pages =        "23:1--23:??",
  month =        oct,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2665068",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Nov 6 16:08:07 MST 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Developing and deploying Web applications on networked
                 embedded devices is often seen as a way to reduce the
                 development cost and time to market for new target
                 platforms. However, the size of the messages and the
                 processing requirements of today's Web protocols, such
                 as HTTP and XML, are challenging for the most
                 resource-constrained class of devices that could also
                 benefit from Web connectivity. New Web protocols using
                 binary representations have been proposed for
                 addressing this issue. Constrained Application Protocol
                 (CoAP) reduces the bandwidth and processing
                 requirements compared to HTTP while preserving the core
                 concepts of the Web architecture. Similarly, Efficient
                 XML Interchange (EXI) format has been standardized for
                 reducing the size and processing time for XML
                 structured information. Nevertheless, the adoption of
                 these technologies is lagging behind due to lack of
                 support from Web browsers and current Web development
                 toolkits. Motivated by these problems, this article
                 presents the design and implementation techniques for
                 the EXIP framework for embedded Web development. The
                 framework consists of a highly efficient EXI processor,
                 a tool for EXI data binding based on templates, and a
                 CoAP/EXI/XHTML Web page engine. A prototype
                 implementation of the EXI processor is herein presented
                 and evaluated. It can be applied to Web browsers or
                 thin server platforms using XHTML and Web services for
                 supporting human-machine interactions in the Internet
                 of Things. This article contains four major results:
                 (1) theoretical and practical evaluation of the use of
                 binary protocols for embedded Web programming; (2) a
                 novel method for generation of EXI grammars based on
                 XML Schema definitions; (3) an algorithm for grammar
                 concatenation that produces normalized EXI grammars
                 directly, and hence reduces the number of iterations
                 during grammar generation; (4) an algorithm for
                 efficient representation of possible deviations from
                 the XML schema.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "23",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Thomas:2014:UID,
  author =       "Paul Thomas",
  title =        "Using Interaction Data to Explain Difficulty
                 Navigating Online",
  journal =      j-TWEB,
  volume =       "8",
  number =       "4",
  pages =        "24:1--24:??",
  month =        oct,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2656343",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Nov 6 16:08:07 MST 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "A user's behaviour when browsing a Web site contains
                 clues to that user's experience. It is possible to
                 record some of these behaviours automatically, and
                 extract signals that indicate a user is having trouble
                 finding information. This allows for Web site analytics
                 based on user experiences, not just page impressions. A
                 series of experiments identified user browsing
                 behaviours-such as time taken and amount of scrolling
                 up a page-which predict navigation difficulty and which
                 can be recorded with minimal or no changes to existing
                 sites or browsers. In turn, patterns of page views
                 correlate with these signals and these patterns can
                 help Web authors understand where and why their sites
                 are hard to navigate. A new software tool, ``LATTE,''
                 automates this analysis and makes it available to Web
                 authors in the context of the site itself.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "24",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{White:2014:CBO,
  author =       "Ryen W. White and Ahmed Hassan",
  title =        "Content Bias in Online Health Search",
  journal =      j-TWEB,
  volume =       "8",
  number =       "4",
  pages =        "25:1--25:??",
  month =        oct,
  year =         "2014",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2663355",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Nov 6 16:08:07 MST 2014",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Search engines help people answer consequential
                 questions. Biases in retrieved and indexed content
                 (e.g., skew toward erroneous outcomes that represent
                 deviations from reality), coupled with searchers'
                 biases in how they examine and interpret search
                 results, can lead people to incorrect answers. In this
                 article, we seek to better understand biases in search
                 and retrieval, and in particular those affecting the
                 accuracy of content in search results, including the
                 search engine index, features used for ranking, and the
                 formulation of search queries. Focusing on the
                 important domain of online health search, this research
                 broadens previous work on biases in search to examine
                 the role of search systems in contributing to biases.
                 To assess bias, we focus on questions about medical
                 interventions and employ reliable ground truth data
                 from authoritative medical sources. In the course of
                 our study, we utilize large-scale log analysis using
                 data from a popular Web search engine, deep probes of
                 result lists on that search engine, and crowdsourced
                 human judgments of search result captions and landing
                 pages. Our findings reveal bias in results, amplifying
                 searchers' existing biases that appear evident in their
                 search activity. We also highlight significant bias in
                 indexed content and show that specific ranking signals
                 and specific query terms support bias. Both of these
                 can degrade result accuracy and increase skewness in
                 search results. Our analysis has implications for bias
                 mitigation strategies in online search systems, and we
                 offer recommendations for search providers based on our
                 findings.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "25",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Fletcher:2015:EPN,
  author =       "Kenneth K. Fletcher and Xiaoqing F. Liu and Mingdong
                 Tang",
  title =        "Elastic Personalized Nonfunctional Attribute
                 Preference and Trade-off Based Service Selection",
  journal =      j-TWEB,
  volume =       "9",
  number =       "1",
  pages =        "1:1--1:??",
  month =        jan,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2697389",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Jan 23 17:41:52 MST 2015",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "For service users to get the best service that meet
                 their requirements, they prefer to personalize their
                 nonfunctional attributes, such as reliability and
                 price. However, the personalization makes it
                 challenging for service providers to completely meet
                 users' preferences, because they have to deal with
                 conflicting nonfunctional attributes when selecting
                 services for users. With this in mind, users may
                 sometimes want to explicitly specify their trade-offs
                 among nonfunctional attributes to make their
                 preferences known to service providers. In this
                 article, we present a novel service selection method
                 based on fuzzy logic that considers users' personalized
                 preferences and their trade-offs on nonfunctional
                 attributes during service selection. The method allows
                 users to represent their elastic nonfunctional
                 requirements and associated importance using linguistic
                 terms to specify their personalized trade-off
                 strategies. We present examples showing how the service
                 selection framework is used and a prototype with
                 real-world airline services to evaluate the proposed
                 framework's application.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "1",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Zhang:2015:REA,
  author =       "Haibin Zhang and Yan Wang and Xiuzhen Zhang and
                 Ee-Peng Lim",
  title =        "{ReputationPro}: The Efficient Approaches to
                 Contextual Transaction Trust Computation in
                 {E}-Commerce Environments",
  journal =      j-TWEB,
  volume =       "9",
  number =       "1",
  pages =        "2:1--2:??",
  month =        jan,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2697390",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Jan 23 17:41:52 MST 2015",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "In e-commerce environments, the trustworthiness of a
                 seller is utterly important to potential buyers,
                 especially when a seller is not known to them. Most
                 existing trust evaluation models compute a single value
                 to reflect the general trustworthiness of a seller
                 without taking any transaction context information into
                 account. With such a result as the indication of
                 reputation, a buyer may be easily deceived by a
                 malicious seller in a transaction where the notorious
                 value imbalance problem is involved-in other words, a
                 malicious seller accumulates a high-level reputation by
                 selling cheap products and then deceives buyers by
                 inducing them to purchase more expensive products. In
                 this article, we first present a trust vector
                 consisting of three values for contextual transaction
                 trust (CTT). In the computation of CTT values, three
                 identified important context dimensions, including
                 Product Category, Transaction Amount, and Transaction
                 Time, are taken into account. In the meantime, the
                 computation of each CTT value is based on both past
                 transactions and the forthcoming transaction. In
                 particular, with different parameters specified by a
                 buyer regarding context dimensions, different sets of
                 CTT values can be calculated. As a result, all of these
                 trust values can outline the reputation profile of a
                 seller that indicates the dynamic trustworthiness of a
                 seller in different products, product categories, price
                 ranges, time periods, and any necessary combination of
                 them. We name this new model ReputationPro.
                 Nevertheless, in ReputationPro, the computation of
                 reputation profile requires new data structures for
                 appropriately indexing the precomputation of aggregates
                 over large-scale ratings and transaction data in three
                 context dimensions, as well as novel algorithms for
                 promptly answering buyers' CTT queries. In addition,
                 storing precomputed aggregation results consumes a
                 large volume of space, particularly for a system with
                 millions of sellers. Therefore, reducing storage space
                 for aggregation results is also a great demand. To
                 solve these challenging problems, we first propose a
                 new index scheme CMK-tree by extending the
                 two-dimensional K-D-B-tree that indexes spatial data to
                 support efficient computation of CTT values. Then, we
                 further extend the CMK-tree and propose a
                 CMK-tree$^{RS}$ approach to reducing the storage space
                 allocated to each seller. The two approaches are not
                 only applicable to three context dimensions that are
                 either linear or hierarchical but also take into
                 account the characteristics of the transaction-time
                 model-that is, transaction data is inserted in
                 chronological order. Moreover, the proposed data
                 structures can index each specific product traded in a
                 time period to compute the trustworthiness of a seller
                 in selling a product. Finally, the experimental results
                 illustrate that the CMK-tree is superior in efficiency
                 of computing CTT values to all three existing
                 approaches in the literature. In particular, while
                 answering a buyer's CTT queries for each brand-based
                 product category, the CMK-tree has almost linear query
                 performance. In addition, with significantly reduced
                 storage space, the CMK-tree$^{RS}$ approach can further
                 improve the efficiency in computing CTT values.
                 Therefore, our proposed ReputationPro model is scalable
                 to large-scale e-commerce Web sites in terms of
                 efficiency and storage space consumption.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "2",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Cai:2015:ALW,
  author =       "Wenbin Cai and Muhan Zhang and Ya Zhang",
  title =        "Active Learning for {Web} Search Ranking via Noise
                 Injection",
  journal =      j-TWEB,
  volume =       "9",
  number =       "1",
  pages =        "3:1--3:??",
  month =        jan,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2697391",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Jan 23 17:41:52 MST 2015",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Learning to rank has become increasingly important for
                 many information retrieval applications. To reduce the
                 labeling cost at training data preparation, many active
                 sampling algorithms have been proposed. In this
                 article, we propose a novel active learning-for-ranking
                 strategy called ranking-based sensitivity sampling
                 (RSS), which is tailored for Gradient Boosting Decision
                 Tree (GBDT), a machine-learned ranking method widely
                 used in practice by major commercial search engines for
                 ranking. We leverage the property of GBDT that samples
                 close to the decision boundary tend to be sensitive to
                 perturbations and design the active learning strategy
                 accordingly. We further theoretically analyze the
                 proposed strategy by exploring the connection between
                 the sensitivity used for sample selection and model
                 regularization to provide a potentially theoretical
                 guarantee w.r.t. the generalization capability.
                 Considering that the performance metrics of ranking
                 overweight the top-ranked items, item rank is
                 incorporated into the selection function. In addition,
                 we generalize the proposed technique to several other
                 base learners to show its potential applicability in a
                 wide variety of applications. Substantial experimental
                 results on both the benchmark dataset and a real-world
                 dataset have demonstrated that our proposed active
                 learning strategy is highly effective in selecting the
                 most informative examples.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "3",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Gill:2015:CWC,
  author =       "Phillipa Gill and Masashi Crete-Nishihata and Jakub
                 Dalek and Sharon Goldberg and Adam Senft and Greg
                 Wiseman",
  title =        "Characterizing {Web} Censorship Worldwide: Another
                 Look at the {OpenNet} Initiative Data",
  journal =      j-TWEB,
  volume =       "9",
  number =       "1",
  pages =        "4:1--4:??",
  month =        jan,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2700339",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Jan 23 17:41:52 MST 2015",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "In this study, we take another look at 5 years of web
                 censorship data gathered by the OpenNet Initiative in
                 77 countries using user-based testing with locally
                 relevant content. Prior to our work, this data had been
                 analyzed with little automation, focusing on what
                 content had been blocked, rather than how blocking was
                 carried out. In this study, we use more rigorous
                 automation to obtain a longitudinal, global view of the
                 technical means used for web censorship. We also
                 identify blocking that had been missed in prior
                 analyses. Our results point to considerable variability
                 in the technologies used for web censorship, across
                 countries, time, and types of content, and even across
                 ISPs in the same country. In addition to characterizing
                 web censorship in countries that, thus far, have eluded
                 technical analysis, we also discuss the implications of
                 our observations on the design of future network
                 measurement platforms and circumvention technologies.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "4",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Fionda:2015:NFL,
  author =       "Valeria Fionda and Giuseppe Pirr{\`o} and Claudio
                 Gutierrez",
  title =        "{NautiLOD}: a Formal Language for the {Web of Data}
                 Graph",
  journal =      j-TWEB,
  volume =       "9",
  number =       "1",
  pages =        "5:1--5:??",
  month =        jan,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2697393",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Jan 23 17:41:52 MST 2015",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The Web of Linked Data is a huge graph of distributed
                 and interlinked datasources fueled by structured
                 information. This new environment calls for formal
                 languages and tools to automatize navigation across
                 datasources (nodes in such graph) and enable
                 semantic-aware and Web-scale search mechanisms. In this
                 article we introduce a declarative navigational
                 language for the Web of Linked Data graph called N
                 autiLOD. NautiLOD enables one to specify datasources
                 via the intertwining of navigation and querying
                 capabilities. It also features a mechanism to specify
                 actions (e.g., send notification messages) that obtain
                 their parameters from datasources reached during the
                 navigation. We provide a formalization of the NautiLOD
                 semantics, which captures both nodes and fragments of
                 the Web of Linked Data. We present algorithms to
                 implement such semantics and study their computational
                 complexity. We discuss an implementation of the
                 features of NautiLOD in a tool called swget, which
                 exploits current Web technologies and protocols. We
                 report on the evaluation of swget and its comparison
                 with related work. Finally, we show the usefulness of
                 capturing Web fragments by providing examples in
                 different knowledge domains.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "5",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Anonymous:2015:E,
  author =       "Anonymous",
  title =        "Editorial",
  journal =      j-TWEB,
  volume =       "9",
  number =       "2",
  pages =        "6:1--6:??",
  month =        may,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2755995",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed May 27 10:18:18 MDT 2015",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "6",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Tranquillini:2015:MEI,
  author =       "Stefano Tranquillini and Florian Daniel and Pavel
                 Kucherbaev and Fabio Casati",
  title =        "Modeling, Enacting, and Integrating Custom
                 Crowdsourcing Processes",
  journal =      j-TWEB,
  volume =       "9",
  number =       "2",
  pages =        "7:1--7:??",
  month =        may,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2746353",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed May 27 10:18:18 MDT 2015",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Crowdsourcing (CS) is the outsourcing of a unit of
                 work to a crowd of people via an open call for
                 contributions. Thanks to the availability of online CS
                 platforms, such as Amazon Mechanical Turk or
                 CrowdFlower, the practice has experienced a tremendous
                 growth over the past few years and demonstrated its
                 viability in a variety of fields, such as data
                 collection and analysis or human computation. Yet it is
                 also increasingly struggling with the inherent
                 limitations of these platforms: each platform has its
                 own logic of how to crowdsource work (e.g., marketplace
                 or contest), there is only very little support for
                 structured work (work that requires the coordination of
                 multiple tasks), and it is hard to integrate
                 crowdsourced tasks into state-of-the-art business
                 process management (BPM) or information systems. We
                 attack these three shortcomings by (1) developing a
                 flexible CS platform (we call it Crowd Computer, or CC)
                 that allows one to program custom CS logics for
                 individual and structured tasks, (2) devising a
                 BPMN--based modeling language that allows one to
                 program CC intuitively, (3) equipping the language with
                 a dedicated visual editor, and (4) implementing CC on
                 top of standard BPM technology that can easily be
                 integrated into existing software and processes. We
                 demonstrate the effectiveness of the approach with a
                 case study on the crowd-based mining of mashup model
                 patterns.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "7",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Diaz:2015:AWR,
  author =       "Oscar D{\'\i}az and Crist{\'o}bal Arellano",
  title =        "The Augmented {Web}: Rationales, Opportunities, and
                 Challenges on Browser-Side Transcoding",
  journal =      j-TWEB,
  volume =       "9",
  number =       "2",
  pages =        "8:1--8:??",
  month =        may,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2735633",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed May 27 10:18:18 MDT 2015",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Today's web personalization technologies use
                 approaches like user categorization, configuration, and
                 customization but do not fully support individualized
                 requirements. As a significant portion of our social
                 and working interactions are migrating to the web, we
                 can expect an increase in these kinds of minority
                 requirements. Browser-side transcoding holds the
                 promise of facilitating this aim by opening
                 personalization to third parties through web
                 augmentation (WA), realized in terms of extensions and
                 userscripts. WA is to the web what augmented reality is
                 to the physical world: to layer relevant
                 content/layout/navigation over the existing web to
                 improve the user experience. From this perspective, WA
                 is not as powerful as web personalization since its
                 scope is limited to the surface of the web. However, it
                 permits this surface to be tuned by developers other
                 than the sites' webmasters. This opens up the web to
                 third parties who might come up with imaginative ways
                 of adapting the web surface for their own purposes. Its
                 success is backed up by millions of downloads. This
                 work looks at this phenomenon, delving into the
                 ``what,'' the ``why,'' and the ``what for'' of WA, and
                 surveys the challenges ahead for WA to thrive. To this
                 end, we appraise the most downloaded 45 WA extensions
                 for Mozilla Firefox and Google Chrome as well as
                 conduct a systematic literature review to identify what
                 quality issues received the most attention in the
                 literature. The aim is to raise awareness about WA as a
                 key enabler of the personal web and point out research
                 directions.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "8",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Sun:2015:ITB,
  author =       "Chang-Ai Sun and Xin Zhang and Yan Shang and Marco
                 Aiello",
  title =        "Integrating Transactions into {BPEL} Service
                 Compositions: an Aspect-Based Approach",
  journal =      j-TWEB,
  volume =       "9",
  number =       "2",
  pages =        "9:1--9:??",
  month =        may,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2757288",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed May 27 10:18:18 MDT 2015",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The concept of software as a service has been
                 increasingly adopted to develop distributed
                 applications. Ensuring the reliability of loosely
                 coupled compositions is a challenging task because of
                 the open, dynamic, and independent nature of composable
                 services; this is especially true when the execution of
                 a service-based process relies on independent but
                 correlated services. Transactions are the prototypical
                 case of compositions spanning across multiple services
                 and needing properties to be valid throughout the whole
                 execution. Although transaction protocols and service
                 composition languages have been proposed in the past
                 decade, a true viable and effective solution is still
                 missing. In this article, we propose a systematic
                 aspect-based approach to integrating transactions into
                 service compositions, taking into account the
                 well-known protocols: Web Service Transaction and
                 Business Process Execution Language (BPEL). In our
                 approach, transaction policies are first defined as a
                 set of aspects. They are then converted to standard
                 BPEL elements. Finally, these transaction-related
                 elements and the original BPEL process are weaved
                 together, resulting in a transactional executable BPEL
                 process. At runtime, transaction management is the
                 responsibility of a middleware, which implements the
                 coordination framework and transaction protocols
                 followed by the transactional BPEL process and
                 transaction-aware Web services. To automate the
                 proposed approach, we developed a supporting platform
                 called Salan to aid the tasks of defining, validating,
                 and weaving aspect-based transaction policies, and of
                 deploying the transactional BPEL processes. By means of
                 a case study, we demonstrate the proposed approach and
                 evaluate the performance of the supporting platform.
                 Experimental results show that this approach is
                 effective in producing reliable business processes
                 while reducing the need for direct human involvement.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "9",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Kwasnikowska:2015:FAO,
  author =       "Natalia Kwasnikowska and Luc Moreau and Jan {Van Den
                 Bussche}",
  title =        "A Formal Account of the Open Provenance Model",
  journal =      j-TWEB,
  volume =       "9",
  number =       "2",
  pages =        "10:1--10:??",
  month =        may,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2734116",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed May 27 10:18:18 MDT 2015",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "On the Web, where resources such as documents and data
                 are published, shared, transformed, and republished,
                 provenance is a crucial piece of metadata that would
                 allow users to place their trust in the resources they
                 access. The open provenance model (OPM) is a community
                 data model for provenance that is designed to
                 facilitate the meaningful interchange of provenance
                 information between systems. Underpinning OPM is a
                 notion of directed graph, where nodes represent data
                 products and processes involved in past computations
                 and edges represent dependencies between them; it is
                 complemented by graphical inference rules allowing new
                 dependencies to be derived. Until now, however, the OPM
                 model was a purely syntactical endeavor. The present
                 article extends OPM graphs with an explicit distinction
                 between precise and imprecise edges. Then a formal
                 semantics for the thus enriched OPM graphs is proposed,
                 by viewing OPM graphs as temporal theories on the
                 temporal events represented in the graph. The original
                 OPM inference rules are scrutinized in view of the
                 semantics and found to be sound but incomplete. An
                 extended set of graphical rules is provided and proved
                 to be complete for inference. The article concludes
                 with applications of the formal semantics to
                 inferencing in OPM graphs, operators on OPM graphs, and
                 a formal notion of refinement among OPM graphs.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "10",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Cappiello:2015:UCA,
  author =       "Cinzia Cappiello and Maristella Matera and Matteo
                 Picozzi",
  title =        "A {UI}-Centric Approach for the End-User Development
                 of Multidevice Mashups",
  journal =      j-TWEB,
  volume =       "9",
  number =       "3",
  pages =        "11:1--11:??",
  month =        jun,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2735632",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Aug 7 10:27:41 MDT 2015",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "In recent years, models, composition paradigms, and
                 tools for mashup development have been proposed to
                 support the integration of information sources,
                 services and APIs available on the Web. The challenge
                 is to provide a gate to a ``programmable Web,'' where
                 end users are allowed to construct easily composite
                 applications that merge content and functions so as to
                 satisfy the long tail of their specific needs. The
                 approaches proposed so far do not fully accommodate
                 this vision. This article, therefore, proposes a mashup
                 development framework that is oriented toward the
                 End-User Development. Given the fundamental role of
                 user interfaces (UIs) as a medium easily understandable
                 by the end users, the proposed approach is
                 characterized by UI-centric models able to support a
                 WYSIWYG (What You See Is What You Get) specification of
                 data integration and service orchestration. It,
                 therefore, contributes to the definition of adequate
                 abstractions that, by hiding the technology and
                 implementation complexity, can be adopted by the end
                 users in a kind of ``democratic'' paradigm for mashup
                 development. This article also shows how model-to-code
                 generative techniques translate models into application
                 schemas, which in turn guide the dynamic instantiation
                 of the composite applications at runtime. This is
                 achieved through lightweight execution environments
                 that can be deployed on the Web and on mobile devices
                 to support the pervasive use of the created
                 applications.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "11",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Zafar:2015:SCO,
  author =       "Muhammad Bilal Zafar and Parantapa Bhattacharya and
                 Niloy Ganguly and Krishna P. Gummadi and Saptarshi
                 Ghosh",
  title =        "Sampling Content from Online Social Networks:
                 Comparing Random vs. Expert Sampling of the {Twitter}
                 Stream",
  journal =      j-TWEB,
  volume =       "9",
  number =       "3",
  pages =        "12:1--12:??",
  month =        jun,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2743023",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Aug 7 10:27:41 MDT 2015",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Analysis of content streams gathered from social
                 networking sites such as Twitter has several
                 applications ranging from content search and
                 recommendation, news detection to business analytics.
                 However, processing large amounts of data generated on
                 these sites in real-time poses a difficult challenge.
                 To cope with the data deluge, analytics companies and
                 researchers are increasingly resorting to sampling. In
                 this article, we investigate the crucial question of
                 how to sample content streams generated by users in
                 online social networks. The traditional method is to
                 randomly sample all the data. For example, most studies
                 using Twitter data today rely on the 1\% and 10\%
                 randomly sampled streams of tweets that are provided by
                 Twitter. In this paper, we analyze a different sampling
                 methodology, one where content is gathered only from a
                 relatively small sample ($< 1\%$) of the user
                 population, namely, the expert users. Over the duration
                 of a month, we gathered tweets from over 500,000
                 Twitter users who are identified as experts on a
                 diverse set of topics, and compared the resulting
                 expert sampled tweets with the 1\% randomly sampled
                 tweets provided publicly by Twitter. We compared the
                 sampled datasets along several dimensions, including
                 the popularity, topical diversity, trustworthiness, and
                 timeliness of the information contained within them,
                 and on the sentiment/opinion expressed on specific
                 topics. Our analysis reveals several important
                 differences in data obtained through the different
                 sampling methodologies, which have serious implications
                 for applications such as topical search, trustworthy
                 content recommendations, breaking news detection, and
                 opinion mining.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "12",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Wang:2015:SWU,
  author =       "Yazhe Wang and Jamie Callan and Baihua Zheng",
  title =        "Should We Use the Sample? {Analyzing} Datasets Sampled
                 from {Twitter}'s Stream {API}",
  journal =      j-TWEB,
  volume =       "9",
  number =       "3",
  pages =        "13:1--13:??",
  month =        jun,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2746366",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Aug 7 10:27:41 MDT 2015",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Researchers have begun studying content obtained from
                 microblogging services such as Twitter to address a
                 variety of technological, social, and commercial
                 research questions. The large number of Twitter users
                 and even larger volume of tweets often make it
                 impractical to collect and maintain a complete record
                 of activity; therefore, most research and some
                 commercial software applications rely on samples, often
                 relatively small samples, of Twitter data. For the most
                 part, sample sizes have been based on availability and
                 practical considerations. Relatively little attention
                 has been paid to how well these samples represent the
                 underlying stream of Twitter data. To fill this gap,
                 this article performs a comparative analysis on samples
                 obtained from two of Twitter's streaming APIs with a
                 more complete Twitter dataset to gain an in-depth
                 understanding of the nature of Twitter data samples and
                 their potential for use in various data mining tasks.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "13",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Su:2015:RRT,
  author =       "Zhiyuan Su and Ling Liu and Mingchu Li and Xinxin Fan
                 and Yang Zhou",
  title =        "Reliable and Resilient Trust Management in Distributed
                 Service Provision Networks",
  journal =      j-TWEB,
  volume =       "9",
  number =       "3",
  pages =        "14:1--14:??",
  month =        jun,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2754934",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Aug 7 10:27:41 MDT 2015",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Distributed service networks are popular platforms for
                 service providers to offer services to consumers and
                 for service consumers to acquire services from unknown
                 parties. eBay and Amazon are two well-known examples of
                 enabling and hosting such service networks to connect
                 service providers to service consumers. Trust
                 management is a critical component for scaling such
                 distributed service networks to a large and growing
                 number of participants. In this article, we present
                 ServiceTrust$^{++}$, a feedback quality--sensitive and
                 attack resilient trust management scheme for empowering
                 distributed service networks with effective trust
                 management capability. Compared with existing trust
                 models, ServiceTrust$^{++}$ has several novel features.
                 First, we present six attack models to capture both
                 independent and colluding attacks with malicious
                 cliques, malicious spies, and malicious camouflages.
                 Second, we aggregate the feedback ratings based on the
                 variances of participants' feedback behaviors and
                 incorporate feedback similarity as weight into the
                 local trust algorithm. Third, we compute the global
                 trust of a participant by employing conditional trust
                 propagation based on the feedback similarity threshold.
                 This allows ServiceTrust$^{++}$ to control and prevent
                 malicious spies and malicious camouflage peers from
                 boosting their global trust scores by manipulating the
                 feedback ratings of good peers and by taking advantage
                 of the uniform trust propagation. Finally, we
                 systematically combine a trust-decaying strategy with a
                 threshold value--based conditional trust propagation to
                 further strengthen the robustness of our global trust
                 computation against sophisticated malicious feedback.
                 Experimental evaluation with both simulation-based
                 networks and real network dataset Epinion show that
                 ServiceTrust$^{++}$ is highly resilient against all six
                 attack models and highly effective compared to
                 EigenTrust, the most popular and representative trust
                 propagation model to date.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "14",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Calzavara:2015:SLA,
  author =       "Stefano Calzavara and Gabriele Tolomei and Andrea
                 Casini and Michele Bugliesi and Salvatore Orlando",
  title =        "A Supervised Learning Approach to Protect Client
                 Authentication on the {Web}",
  journal =      j-TWEB,
  volume =       "9",
  number =       "3",
  pages =        "15:1--15:??",
  month =        jun,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2754933",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Aug 7 10:27:41 MDT 2015",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Browser-based defenses have recently been advocated as
                 an effective mechanism to protect potentially insecure
                 web applications against the threats of session
                 hijacking, fixation, and related attacks. In existing
                 approaches, all such defenses ultimately rely on
                 client-side heuristics to automatically detect cookies
                 containing session information, to then protect them
                 against theft or otherwise unintended use. While
                 clearly crucial to the effectiveness of the resulting
                 defense mechanisms, these heuristics have not, as yet,
                 undergone any rigorous assessment of their adequacy. In
                 this article, we conduct the first such formal
                 assessment, based on a ground truth of 2,464 cookies we
                 collect from 215 popular websites of the Alexa ranking.
                 To obtain the ground truth, we devise a semiautomatic
                 procedure that draws on the novel notion of
                 authentication token, which we introduce to capture
                 multiple web authentication schemes. We test existing
                 browser-based defenses in the literature against our
                 ground truth, unveiling several pitfalls both in the
                 heuristics adopted and in the methods used to assess
                 them. We then propose a new detection method based on
                 supervised learning, where our ground truth is used to
                 train a set of binary classifiers, and report on
                 experimental evidence that our method outperforms
                 existing proposals. Interestingly, the resulting
                 classifiers, together with our hands-on experience in
                 the construction of the ground truth, provide new
                 insight on how web authentication is actually
                 implemented in practice.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "15",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Lee:2015:DPM,
  author =       "Sihyung Lee",
  title =        "Detection of Political Manipulation in Online
                 Communities through Measures of Effort and
                 Collaboration",
  journal =      j-TWEB,
  volume =       "9",
  number =       "3",
  pages =        "16:1--16:??",
  month =        jun,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2767134",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Aug 7 10:27:41 MDT 2015",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Online social media allow users to interact with one
                 another by sharing opinions, and these opinions have a
                 critical impact on the way readers think and behave.
                 Accordingly, an increasing number of {$<$ i$>$
                 manipulators$<$}/{i$>$} deliberately spread messages to
                 influence the public, often in an organized manner. In
                 particular, political manipulation-manipulation of
                 opponents to win political advantage-can result in
                 serious consequences: antigovernment riots can break
                 out, leading to candidates' defeat in an election. A
                 few approaches have been proposed to detect such
                 manipulation based on the level of social interaction
                 (i.e., manipulators actively post opinions but
                 infrequently befriend and reply to other users).
                 However, several studies have shown that the
                 interactions can be forged at a low cost and thus may
                 not be effective measures of manipulation. To go one
                 step further, we collect a dataset for real,
                 large-scale political manipulation, which consists of
                 opinions found on Internet forums. These opinions are
                 divided into manipulators and nonmanipulators. Using
                 this collection, we demonstrate that manipulators
                 inevitably work hard, in teams, to quickly influence a
                 large audience. With this in mind, it could be said
                 that a high level of collaborative efforts strongly
                 indicates manipulation. For example, a group of
                 manipulators may jointly post numerous opinions with a
                 consistent theme and selectively recommend the same,
                 well-organized opinion to promote its rank. We show
                 that the effort measures, when combined with a
                 supervised learning algorithm, successfully identify
                 greater than 95\% of the manipulators. We believe that
                 the proposed method will help system administrators to
                 accurately detect manipulators in disguise,
                 significantly decreasing the intensity of
                 manipulation.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "16",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Gollapalli:2015:IRH,
  author =       "Sujatha Das Gollapalli and Cornelia Caragea and
                 Prasenjit Mitra and C. Lee Giles",
  title =        "Improving Researcher Homepage Classification with
                 Unlabeled Data",
  journal =      j-TWEB,
  volume =       "9",
  number =       "4",
  pages =        "17:1--17:??",
  month =        oct,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2767135",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Jan 25 07:43:09 MST 2016",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/hash.bib;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "A classifier that determines if a webpage is relevant
                 to a specified set of topics comprises a key component
                 for focused crawling. Can a classifier that is tuned to
                 perform well on training datasets continue to filter
                 out irrelevant pages in the face of changing content on
                 the Web? We investigate this question in the context of
                 identifying researcher homepages. We show
                 experimentally that classifiers trained on existing
                 datasets of academic homepages underperform on
                 ``non-homepages'' present on current-day academic
                 websites. As an alternative to obtaining labeled
                 datasets to retrain classifiers for the new content, in
                 this article we ask the following question: ``How can
                 we effectively use the unlabeled data readily available
                 from academic websites to improve researcher homepage
                 classification?'' We design novel URL-based features
                 and use them in conjunction with content-based features
                 for representing homepages. Within the co-training
                 framework, these sets of features can be treated as
                 complementary views enabling us to effectively use
                 unlabeled data and obtain remarkable improvements in
                 homepage identification on the current-day academic
                 websites. We also propose a novel technique for
                 ``learning a conforming pair of classifiers'' that
                 mimics co-training. Our algorithm seeks to minimize a
                 loss (objective) function quantifying the difference in
                 predictions from the two views afforded by co-training.
                 We argue that this loss formulation provides insights
                 for understanding co-training and can be used even in
                 the absence of a validation dataset. Our next set of
                 findings pertains to the evaluation of other
                 state-of-the-art techniques for classifying homepages.
                 First, we apply feature selection (FS) and feature
                 hashing (FH) techniques independently and in
                 conjunction with co-training to academic homepages. FS
                 is a well-known technique for removing redundant and
                 unnecessary features from the data representation,
                 whereas FH is a technique that uses hash functions for
                 efficient encoding of features. We show that FS can be
                 effectively combined with co-training to obtain further
                 improvements in identifying homepages. However, using
                 hashed feature representations, a performance
                 degradation is observed possibly due to feature
                 collisions. Finally, we evaluate other semisupervised
                 algorithms for homepage classification. We show that
                 although several algorithms are effective in using
                 information from the unlabeled instances, co-training
                 that explicitly harnesses the feature split in the
                 underlying instances outperforms approaches that
                 combine content and URL features into a single view.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "17",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Wang:2015:DCU,
  author =       "Jing Wang and Clement T. Yu and Philip S. Yu and Bing
                 Liu and Weiyi Meng",
  title =        "Diversionary Comments under Blog Posts",
  journal =      j-TWEB,
  volume =       "9",
  number =       "4",
  pages =        "18:1--18:??",
  month =        oct,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2789211",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Jan 25 07:43:09 MST 2016",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "There has been a recent swell of interest in the
                 analysis of blog comments. However, much of the work
                 focuses on detecting comment spam in the blogsphere. An
                 important issue that has been neglected so far is the
                 identification of diversionary comments. Diversionary
                 comments are defined as comments that divert the topic
                 from the original post. A possible purpose is to
                 distract readers from the original topic and draw
                 attention to a new topic. We categorize diversionary
                 comments into five types based on our observations and
                 propose an effective framework to identify and flag
                 them. To the best of our knowledge, the problem of
                 detecting diversionary comments has not been studied so
                 far. We solve the problem in two different ways: (i)
                 rank all comments in descending order of being
                 diversionary and (ii) consider it as a classification
                 problem. Our evaluation on 4,179 comments under 40
                 different blog posts from Digg and Reddit shows that
                 the proposed method achieves the high mean average
                 precision of 91.9\% when the problem is considered as a
                 ranking problem and 84.9\% of F-measure as a
                 classification problem. Sensitivity analysis indicates
                 that the effectiveness of the method is stable under
                 different parameter settings.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "18",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Katzir:2015:ECC,
  author =       "Liran Katzir and Stephen J. Hardiman",
  title =        "Estimating Clustering Coefficients and Size of Social
                 Networks via Random Walk",
  journal =      j-TWEB,
  volume =       "9",
  number =       "4",
  pages =        "19:1--19:??",
  month =        oct,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2790304",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Jan 25 07:43:09 MST 2016",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "This work addresses the problem of estimating social
                 network measures. Specifically, the measures at hand
                 are the network average and global clustering
                 coefficients and the number of registered users. The
                 algorithms at hand (1) assume no prior knowledge about
                 the network and (2) access the network using only the
                 publicly available interface. More precisely, this work
                 provides (a) a unified approach for clustering
                 coefficients estimation and (b) a new network size
                 estimator. The unified approach for the clustering
                 coefficients yields the first external access algorithm
                 for estimating the global clustering coefficient. The
                 new network size estimator offers improved accuracy
                 compared to prior art estimators. Our approach is to
                 view a social network as an undirected graph and use
                 the public interface to retrieve a random walk. To
                 estimate the clustering coefficient, the connectivity
                 of each node in the random walk sequence is tested in
                 turn. We show that the error drops exponentially in the
                 number of random walk steps. For the network size
                 estimation we offer a generalized view of prior art
                 estimators that in turn yields an improved estimator.
                 All algorithms are validated on several publicly
                 available social network datasets.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "19",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Watanabe:2015:FQM,
  author =       "Willian Massami Watanabe and Ana Luiza Dias and Renata
                 Pontin {De Mattos Fortes}",
  title =        "{Fona}: Quantitative Metric to Measure Focus
                 Navigation on Rich {Internet} Applications",
  journal =      j-TWEB,
  volume =       "9",
  number =       "4",
  pages =        "20:1--20:??",
  month =        oct,
  year =         "2015",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2812812",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Jan 25 07:43:09 MST 2016",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The Web 2.0 brought new requirements to the
                 architecture of web systems. Web applications'
                 interfaces are becoming more and more interactive.
                 However, these changes are severely impacting how
                 disabled users interact through assistive technologies
                 with the web. In order to deploy an accessible web
                 application, developers can use WAI-ARIA to design an
                 accessible web application, which manually implements
                 focus and keyboard navigation mechanisms. This article
                 presents a quantitative metric, named Fona, which
                 measures how the Focus Navigation WAI-ARIA requirement
                 has been implemented on the web. Fona counts JavaScript
                 mouse event listeners, HTML elements with role
                 attributes, and TabIndex attributes in the DOM
                 structure of webpages. Fona's evaluation approach
                 provides a narrow analysis of one single accessibility
                 requirement. But it enables monitoring this
                 accessibility requirement in a large number of
                 webpages. This monitoring activity might be used to
                 give insights about how Focus Navigation and ARIA
                 requirements have been considered by web development
                 teams. Fona is validated comparing the results of a set
                 of WAI-ARIA conformant implementations and a set of
                 webpages formed by Alexa's 349 top most popular
                 websites. The analysis of Fona's value for Alexa's
                 websites highlights that many websites still lack the
                 implementation of Focus Navigation through their
                 JavaScript interactive content.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "20",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Marszalkowski:2016:ASC,
  author =       "Jakub Marszalkowski and Jan Mizgajski and Dariusz
                 Mokwa and Maciej Drozdowski",
  title =        "Analysis and Solution of {CSS}-Sprite Packing
                 Problem",
  journal =      j-TWEB,
  volume =       "10",
  number =       "1",
  pages =        "1:1--1:??",
  month =        feb,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2818377",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed May 25 17:02:04 MDT 2016",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "A CSS-sprite packing problem is considered in this
                 article. CSS-sprite is a technique of combining many
                 pictures of a web page into one image for the purpose
                 of reducing network transfer time. The CSS-sprite
                 packing problem is formulated here as an optimization
                 challenge. The significance of geometric packing, image
                 compression and communication performance is discussed.
                 A mathematical model for constructing multiple sprites
                 and optimization of load time is proposed. The impact
                 of PNG-sprite aspect ratio on file size is studied
                 experimentally. Benchmarking of real user web browsers
                 communication performance covers latency, bandwidth,
                 number of concurrent channels as well as speedup from
                 parallel download. Existing software for building
                 CSS-sprites is reviewed. A novel method, called
                 Spritepack, is proposed and evaluated. Spritepack
                 outperforms current software.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "1",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Amor:2016:DBT,
  author =       "Iheb Ben Amor and Salima Benbernou and Mourad Ouziri
                 and Zaki Malik and Brahim Medjahed",
  title =        "Discovering Best Teams for Data Leak-Aware
                 Crowdsourcing in Social Networks",
  journal =      j-TWEB,
  volume =       "10",
  number =       "1",
  pages =        "2:1--2:??",
  month =        feb,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2814573",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed May 25 17:02:04 MDT 2016",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Crowdsourcing is emerging as a powerful paradigm to
                 help perform a wide range of tedious tasks in various
                 enterprise applications. As such applications become
                 more complex, crowdsourcing systems often require the
                 collaboration of several experts connected through
                 professional/social networks and organized in various
                 teams. For instance, a well-known car manufacturer
                 asked fans to contribute ideas for the kinds of
                 technologies that should be incorporated into one of
                 its cars. For that purpose, fans needed to collaborate
                 and form teams competing with each others to come up
                 with the best ideas. However, once teams are formed,
                 each one would like to provide the best solution and
                 treat that solution as a ``trade secret,'' hence
                 preventing any data leak to its competitors (i.e., the
                 other teams). In this article, we propose a data
                 leak--aware crowdsourcing system called SocialCrowd. We
                 introduce a clustering algorithm that uses social
                 relationships between crowd workers to discover all
                 possible teams while avoiding interteam data leakage.
                 We also define a ranking mechanism to select the
                 ``best'' team configurations. Our mechanism is based on
                 the semiring approach defined in the area of soft
                 constraints programming. Finally, we present
                 experiments to assess the efficiency of the proposed
                 approach.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "2",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Song:2016:IJV,
  author =       "Hengjie Song and Yonghui Xu and Huaqing Min and
                 Qingyao Wu and Wei Wei and Jianshu Weng and Xiaogang
                 Han and Qiang Yang and Jialiang Shi and Jiaqian Gu and
                 Chunyan Miao and Nishida Toyoaki",
  title =        "Individual Judgments Versus Consensus: Estimating
                 Query-{URL} Relevance",
  journal =      j-TWEB,
  volume =       "10",
  number =       "1",
  pages =        "3:1--3:??",
  month =        feb,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2834122",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed May 25 17:02:04 MDT 2016",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Query-URL relevance, measuring the relevance of each
                 retrieved URL with respect to a given query, is one of
                 the fundamental criteria to evaluate the performance of
                 commercial search engines. The traditional way to
                 collect reliable and accurate query-URL relevance
                 requires multiple annotators to provide their
                 individual judgments based on their subjective
                 expertise (e.g., understanding of user intents). In
                 this case, the annotators' subjectivity reflected in
                 each annotator individual judgment (AIJ) inevitably
                 affects the quality of the ground truth relevance
                 (GTR). But to the best of our knowledge, the potential
                 impact of AIJs on estimating GTRs has not been studied
                 and exploited quantitatively by existing work. This
                 article first studies how multiple AIJs and GTRs are
                 correlated. Our empirical studies find that the
                 multiple AIJs possibly provide more cues to improve the
                 accuracy of estimating GTRs. Inspired by this finding,
                 we then propose a novel approach to integrating the
                 multiple AIJs with the features characterizing
                 query-URL pairs for estimating GTRs more accurately.
                 Furthermore, we conduct experiments in a commercial
                 search engine-Baidu.com-and report significant gains in
                 terms of the normalized discounted cumulative gains.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "3",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Zhang:2016:DSP,
  author =       "Xianchao Zhang and Zhaoxing Li and Shaoping Zhu and
                 Wenxin Liang",
  title =        "Detecting Spam and Promoting Campaigns in {Twitter}",
  journal =      j-TWEB,
  volume =       "10",
  number =       "1",
  pages =        "4:1--4:??",
  month =        feb,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2846102",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed May 25 17:02:04 MDT 2016",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Twitter has become a target platform for both
                 promoters and spammers to disseminate their messages,
                 which are more harmful than traditional spamming
                 methods, such as email spamming. Recently, large
                 amounts of campaigns that contain lots of spam or
                 promotion accounts have emerged in Twitter. The
                 campaigns cooperatively post unwanted information, and
                 thus they can infect more normal users than individual
                 spam or promotion accounts. Organizing or participating
                 in campaigns has become the main technique to spread
                 spam or promotion information in Twitter. Since
                 traditional solutions focus on checking individual
                 accounts or messages, efficient techniques for
                 detecting spam and promotion campaigns in Twitter are
                 urgently needed. In this article, we propose a
                 framework to detect both spam and promotion campaigns.
                 Our framework consists of three steps: the first step
                 links accounts who post URLs for similar purposes; the
                 second step extracts candidate campaigns that may be
                 for spam or promotion purposes; and the third step
                 classifies the candidate campaigns into normal, spam,
                 and promotion groups. The key point of the framework is
                 how to measure the similarity between accounts'
                 purposes of posting URLs. We present two measure
                 methods based on Shannon information theory: the first
                 one uses the URLs posted by the users, and the second
                 one considers both URLs and timestamps. Experimental
                 results demonstrate that the proposed methods can
                 extract the majority of the candidate campaigns
                 correctly, and detect promotion and spam campaigns with
                 high precision and recall.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "4",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Eshuis:2016:FCE,
  author =       "Rik Eshuis and Freddy L{\'e}cu{\'e} and Nikolay
                 Mehandjiev",
  title =        "Flexible Construction of Executable Service
                 Compositions from Reusable Semantic Knowledge",
  journal =      j-TWEB,
  volume =       "10",
  number =       "1",
  pages =        "5:1--5:??",
  month =        feb,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2842628",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed May 25 17:02:04 MDT 2016",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Most service composition approaches rely on top-down
                 decomposition of a problem and AI-style planning to
                 assemble service components into a meaningful whole,
                 impeding reuse and flexibility. In this article, we
                 propose an approach that starts from declarative
                 knowledge about the semantics of individual service
                 components and algorithmically constructs a full-blown
                 service orchestration process that supports sequence,
                 choice, and parallelism. The output of our algorithm
                 can be mapped directly into a number of service
                 orchestration languages such as OWL-S and BPEL. The
                 approach consists of two steps. First, semantic links
                 specifying data dependencies among the services are
                 derived and organized in a flexible network. Second,
                 based on a user request indicating the desired outcomes
                 from the composition, an executable composition is
                 constructed from the network that satisfies the
                 dependencies. The approach is unique in producing
                 complex compositions out of semantic links between
                 services in a flexible way. It also allows reusing
                 knowledge about semantic dependencies in the network to
                 generate new compositions through new requests and
                 modification of services at runtime. The approach has
                 been implemented in a prototype that outperforms
                 related composition prototypes in experiments.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "5",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Avila:2016:WTC,
  author =       "Bruno T. {\'A}vila and Rafael D. Lins",
  title =        "W-tree: a Compact External Memory Representation for
                 Webgraphs",
  journal =      j-TWEB,
  volume =       "10",
  number =       "1",
  pages =        "6:1--6:??",
  month =        feb,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2835181",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed May 25 17:02:04 MDT 2016",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "World Wide Web applications need to use, constantly
                 update, and maintain large webgraphs for executing
                 several tasks, such as calculating the web impact
                 factor, finding hubs and authorities, performing link
                 analysis by webometrics tools, and ranking webpages by
                 web search engines. Such webgraphs need to use a large
                 amount of main memory, and, frequently, they do not
                 completely fit in, even if compressed. Therefore,
                 applications require the use of external memory. This
                 article presents a new compact representation for
                 webgraphs, called w-tree, which is designed
                 specifically for external memory. It supports the
                 execution of basic queries (e.g., full read, random
                 read, and batch random read), set-oriented queries
                 (e.g., superset, subset, equality, overlap, range,
                 inlink, and co-inlink), and some advanced queries, such
                 as edge reciprocal and hub and authority. Furthermore,
                 a new layout tree designed specifically for webgraphs
                 is also proposed, reducing the overall storage cost and
                 allowing the random read query to be performed with an
                 asymptotically faster runtime in the worst case. To
                 validate the advantages of the w-tree, a series of
                 experiments are performed to assess an implementation
                 of the w-tree comparing it to a compact main memory
                 representation. The results obtained show that w-tree
                 is competitive in compression time and rate and in
                 query time, which may execute several orders of
                 magnitude faster for set-oriented queries than its
                 competitors. The results provide empirical evidence
                 that it is feasible to use a compact external memory
                 representation for webgraphs in real applications,
                 contradicting the previous assumptions made by several
                 researchers.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "6",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Wang:2016:STQ,
  author =       "Xinyu Wang and Jianke Zhu and Zibin Zheng and Wenjie
                 Song and Yuanhong Shen and Michael R. Lyu",
  title =        "A Spatial-Temporal {QoS} Prediction Approach for
                 Time-aware {Web} Service Recommendation",
  journal =      j-TWEB,
  volume =       "10",
  number =       "1",
  pages =        "7:1--7:??",
  month =        feb,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2801164",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed May 25 17:02:04 MDT 2016",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Due to the popularity of service-oriented
                 architectures for various distributed systems, an
                 increasing number of Web services have been deployed
                 all over the world. Recently, Web service
                 recommendation became a hot research topic, one that
                 aims to accurately predict the quality of functional
                 satisfactory services for each end user. Generally, the
                 performance of Web service changes over time due to
                 variations of service status and network conditions.
                 Instead of employing the conventional temporal models,
                 we propose a novel spatial-temporal QoS prediction
                 approach for time-aware Web service recommendation,
                 where a sparse representation is employed to model QoS
                 variations. Specifically, we make a zero-mean Laplace
                 prior distribution assumption on the residuals of the
                 QoS prediction, which corresponds to a Lasso regression
                 problem. To effectively select the nearest neighbor for
                 the sparse representation of temporal QoS values, the
                 geo-location of web service is employed to reduce
                 searching range while improving prediction accuracy.
                 The extensive experimental results demonstrate that the
                 proposed approach outperforms state-of-art methods with
                 more than 10\% improvement on the accuracy of temporal
                 QoS prediction for time-aware Web service
                 recommendation.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "7",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Guo:2016:NEB,
  author =       "Guibing Guo and Jie Zhang and Neil Yorke-Smith",
  title =        "A Novel Evidence-Based {Bayesian} Similarity Measure
                 for Recommender Systems",
  journal =      j-TWEB,
  volume =       "10",
  number =       "2",
  pages =        "8:1--8:??",
  month =        may,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2856037",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed May 25 17:02:04 MDT 2016",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "User-based collaborative filtering, a widely used
                 nearest neighbour-based recommendation technique,
                 predicts an item's rating by aggregating its ratings
                 from similar users. User similarity is traditionally
                 calculated by cosine similarity or the Pearson
                 correlation coefficient. However, both of these
                 measures consider only the direction of rating vectors,
                 and suffer from a range of drawbacks. To overcome these
                 issues, we propose a novel Bayesian similarity measure
                 based on the Dirichlet distribution, taking into
                 consideration both the direction and length of rating
                 vectors. We posit that not all the rating pairs should
                 be equally counted in order to accurately model user
                 correlation. Three different evidence factors are
                 designed to compute the weights of rating pairs.
                 Further, our principled method reduces correlation due
                 to chance and potential system bias. Experimental
                 results on six real-world datasets show that our method
                 achieves superior accuracy in comparison with
                 counterparts.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "8",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Frattolillo:2016:BFM,
  author =       "Franco Frattolillo",
  title =        "A Buyer-Friendly and Mediated Watermarking Protocol
                 for {Web} Context",
  journal =      j-TWEB,
  volume =       "10",
  number =       "2",
  pages =        "9:1--9:??",
  month =        may,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2856036",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed May 25 17:02:04 MDT 2016",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Watermarking protocols are used in conjunction with
                 digital watermarking techniques to protect digital
                 copyright on the Internet. They define the schemes of
                 the web transactions by which buyers can purchase
                 protected digital content distributed by content
                 providers in a secure manner. Over the last few years,
                 significant examples of watermarking protocols have
                 been proposed in literature. However, a detailed
                 examination of such protocols has revealed a number of
                 problems that have to be addressed in order to make
                 them suited for current web context. Therefore, based
                 on the most relevant problems derived from literature,
                 this article identifies the main challenges posed by
                 the development of watermarking protocols for web
                 context and presents a watermarking protocol that
                 follows a new secure, buyer-centric and mediated design
                 approach able to meet such challenges.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "9",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Wu:2016:QDQ,
  author =       "Wensheng Wu and Weiyi Meng and Weifeng Su and Guangyou
                 Zhou and Yao-Yi Chiang",
  title =        "{Q2P}: Discovering Query Templates via
                 Autocompletion",
  journal =      j-TWEB,
  volume =       "10",
  number =       "2",
  pages =        "10:1--10:??",
  month =        may,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2873061",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed May 25 17:02:04 MDT 2016",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "We present Q2P, a system that discovers query
                 templates from search engines via their query
                 autocompletion services. Q2P is distinct from the
                 existing works in that it does not rely on query logs
                 of search engines that are typically not readily
                 available. Q2P is also unique in that it uses a trie to
                 economically store queries sampled from a search engine
                 and employs a beam-search strategy that focuses the
                 expansion of the trie on its most promising nodes.
                 Furthermore, Q2P leverages the trie-based storage of
                 query sample to discover query templates using only two
                 passes over the trie. Q2P is a key part of our ongoing
                 project Deep2Q on a template-driven data integration on
                 the Deep Web, where the templates learned by Q2P are
                 used to guide the integration process in Deep2Q.
                 Experimental results on four major search engines
                 indicate that (1) Q2P sends only a moderate number of
                 queries (ranging from 597 to 1,135) to the engines,
                 while obtaining a significant number of completions per
                 query (ranging from 4.2 to 8.5 on the average); (2) a
                 significant number of templates (ranging from 8 to 32
                 when the minimum support for frequent templates is set
                 to 1\%) may be discovered from the samples.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "10",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Walk:2016:ADC,
  author =       "Simon Walk and Denis Helic and Florian Geigl and
                 Markus Strohmaier",
  title =        "Activity Dynamics in Collaboration Networks",
  journal =      j-TWEB,
  volume =       "10",
  number =       "2",
  pages =        "11:1--11:??",
  month =        may,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2873060",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed May 25 17:02:04 MDT 2016",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Many online collaboration networks struggle to gain
                 user activity and become self-sustaining due to the
                 ramp-up problem or dwindling activity within the
                 system. Prominent examples include online encyclopedias
                 such as (Semantic) MediaWikis, Question and Answering
                 portals such as StackOverflow, and many others. Only a
                 small fraction of these systems manage to reach
                 self-sustaining activity, a level of activity that
                 prevents the system from reverting to a nonactive
                 state. In this article, we model and analyze activity
                 dynamics in synthetic and empirical collaboration
                 networks. Our approach is based on two opposing and
                 well-studied principles: (i) without incentives, users
                 tend to lose interest to contribute and thus, systems
                 become inactive, and (ii) people are susceptible to
                 actions taken by their peers (social or peer
                 influence). With the activity dynamics model that we
                 introduce in this article we can represent typical
                 situations of such collaboration networks. For example,
                 activity in a collaborative network, without external
                 impulses or investments, will vanish over time,
                 eventually rendering the system inactive. However, by
                 appropriately manipulating the activity dynamics and/or
                 the underlying collaboration networks, we can
                 jump-start a previously inactive system and advance it
                 toward an active state. To be able to do so, we first
                 describe our model and its underlying mechanisms. We
                 then provide illustrative examples of empirical
                 datasets and characterize the barrier that has to be
                 breached by a system before it can become
                 self-sustaining in terms of critical mass and activity
                 dynamics. Additionally, we expand on this empirical
                 illustration and introduce a new metric $p$ --- the
                 Activity Momentum --- to assess the activity robustness
                 of collaboration networks.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "11",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Zheng:2016:PQA,
  author =       "Huiyuan Zheng and Jian Yang and Weiliang Zhao",
  title =        "Probabilistic {QoS} Aggregations for Service
                 Composition",
  journal =      j-TWEB,
  volume =       "10",
  number =       "2",
  pages =        "12:1--12:??",
  month =        may,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2876513",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed May 25 17:02:04 MDT 2016",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "In this article, we propose a comprehensive approach
                 for Quality of Service (QoS) calculation in service
                 composition. Differing from the existing work on QoS
                 aggregations that represent QoS as single values,
                 discrete values with frequencies, or standard
                 statistical distributions, the proposed approach has
                 the capability to handle any type of QoS probability
                 distribution. A set of formulae and algorithms are
                 developed to calculate the QoS of a composite service
                 according to four identified basic patterns as
                 sequential, parallel, conditional, and loop. We
                 demonstrate that the proposed QoS calculation method is
                 much more efficient than existing simulation methods.
                 It has a high scalability and builds a solid foundation
                 for real-time QoS analysis and prediction in service
                 composition. Experiment results are provided to show
                 the effectiveness and efficiency of the proposed
                 method.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "12",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Paul:2016:SBC,
  author =       "Michael J. Paul and Ryen W. White and Eric Horvitz",
  title =        "Search and Breast Cancer: On Episodic Shifts of
                 Attention over Life Histories of an Illness",
  journal =      j-TWEB,
  volume =       "10",
  number =       "2",
  pages =        "13:1--13:??",
  month =        may,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2893481",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed May 25 17:02:04 MDT 2016",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "We seek to understand the evolving needs of people who
                 are faced with a life-changing medical diagnosis based
                 on analyses of queries extracted from an anonymized
                 search query log. Focusing on breast cancer, we
                 manually tag a set of Web searchers as showing patterns
                 of search behavior consistent with someone grappling
                 with the screening, diagnosis, and treatment of breast
                 cancer. We build and apply probabilistic classifiers to
                 detect these searchers from multiple sessions and to
                 identify the timing of diagnosis using temporal and
                 statistical features. We explore the changes in
                 information seeking over time before and after an
                 inferred diagnosis of breast cancer by aligning
                 multiple searchers by the estimated time of diagnosis.
                 We employ the classifier to automatically identify
                 1,700 candidate searchers with an estimated 90\%
                 precision, and we predict the day of diagnosis within
                 15 days with an 88\% accuracy. We show that the
                 geographic and demographic attributes of searchers
                 identified with high probability are strongly
                 correlated with ground truth of reported incidence
                 rates. We then analyze the content of queries over time
                 for inferred cancer patients, using a detailed ontology
                 of cancer-related search terms. The analysis reveals
                 the rich temporal structure of the evolving queries of
                 people likely diagnosed with breast cancer. Finally, we
                 focus on subtypes of illness based on inferred stages
                 of cancer and show clinically relevant dynamics of
                 information seeking based on the dominant stage
                 expressed by searchers.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "13",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Doerfel:2016:WUA,
  author =       "Stephan Doerfel and Daniel Zoller and Philipp Singer
                 and Thomas Niebler and Andreas Hotho and Markus
                 Strohmaier",
  title =        "What Users Actually Do in a Social Tagging System: a
                 Study of User Behavior in {BibSonomy}",
  journal =      j-TWEB,
  volume =       "10",
  number =       "2",
  pages =        "14:1--14:??",
  month =        may,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2896821",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed May 25 17:02:04 MDT 2016",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Social tagging systems have established themselves as
                 an important part in today's Web and have attracted the
                 interest of our research community in a variety of
                 investigations. Henceforth, several aspects of social
                 tagging systems have been discussed and assumptions
                 have emerged on which our community builds their work.
                 Yet, testing such assumptions has been difficult due to
                 the absence of suitable usage data in the past. In this
                 work, we thoroughly investigate and evaluate four
                 aspects about tagging systems, covering social
                 interaction, retrieval of posted resources, the
                 importance of the three different types of entities,
                 users, resources, and tags, as well as connections
                 between these entities' popularity in posted and in
                 requested content. For that purpose, we examine live
                 server log data gathered from the real-world, public
                 social tagging system BibSonomy. Our empirical results
                 paint a mixed picture about the four aspects. Although
                 typical assumptions hold to a certain extent for some,
                 other aspects need to be reflected in a very critical
                 light. Our observations have implications for the
                 understanding of social tagging systems and the way
                 they are used on the Web. We make the dataset used in
                 this work available to other researchers.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "14",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Naini:2016:SEW,
  author =       "Kaweh Djafari Naini and Ismail Sengor Altingovde and
                 Wolf Siberski",
  title =        "Scalable and Efficient {Web} Search Result
                 Diversification",
  journal =      j-TWEB,
  volume =       "10",
  number =       "3",
  pages =        "15:1--15:??",
  month =        aug,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2907948",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 3 11:10:09 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "It has been shown that top-$k$ retrieval quality can
                 be considerably improved by taking not only relevance
                 but also diversity into account. However, currently
                 proposed diversification approaches have not put much
                 attention on practical usability in large-scale
                 settings, such as modern web search systems. In this
                 work, we make two contributions toward this goal.
                 First, we propose a combination of optimizations and
                 heuristics for an implicit diversification algorithm
                 based on the desirable facility placement principle,
                 and present two algorithms that achieve linear
                 complexity without compromising the retrieval
                 effectiveness. Instead of an exhaustive comparison of
                 documents, these algorithms first perform a clustering
                 phase and then exploit its outcome to compose the
                 diverse result set. Second, we describe and analyze two
                 variants for distributed diversification in a computing
                 cluster, for large-scale IR where the document
                 collection is too large to keep in one node. Our
                 contribution in this direction is pioneering, as there
                 exists no earlier work in the literature that
                 investigates the effectiveness and efficiency of
                 diversification on a distributed setup. Extensive
                 evaluations on a standard TREC framework demonstrate a
                 competitive retrieval quality of the proposed
                 optimizations to the baseline algorithm while reducing
                 the processing time by more than 80\% and up to 97\%,
                 and shed light on the efficiency and effectiveness
                 tradeoffs of diversification when applied on top of a
                 distributed architecture.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "15",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Furche:2016:PFW,
  author =       "Tim Furche and Giovanni Grasso and Michael Huemer and
                 Christian Schallhart and Michael Schrefl",
  title =        "{PeaCE-Ful} {Web} Event Extraction and Processing as
                 Bitemporal Mutable Events",
  journal =      j-TWEB,
  volume =       "10",
  number =       "3",
  pages =        "16:1--16:??",
  month =        aug,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2911989",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 3 11:10:09 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The web is the largest bulletin board of the world.
                 Events of all types, from flight arrivals to business
                 meetings, are announced on this board. Tracking and
                 reacting to such event announcements, however, is a
                 tedious manual task, only slightly alleviated by email
                 or similar notifications. Announcements are published
                 with human readers in mind, and updates or delayed
                 announcements are frequent. These characteristics have
                 hampered attempts at automatic tracking. P eaCE
                 provides the first integrated framework for event
                 processing on top of web event ads, consisting of event
                 extraction, complex event processing, and action
                 execution in response to these events. Given a schema
                 of the events to be tracked, the framework populates
                 this schema by extracting events from announcement
                 sources. This extraction is performed by little
                 programs called wrappers that produce the events
                 including updates and retractions. PeaCE then queries
                 these events to detect complex events, often combining
                 announcements from multiple sources. To deal with
                 updates and delayed announcements, PeaCE's schemas are
                 bitemporal, to distinguish between occurrence and
                 detection time. This allows complex event
                 specifications to track updates and to react upon
                 differences in occurrence and detection time. In case
                 of new, changing, or deleted events, PeaCE allows one
                 to execute actions, such as tweeting or sending out
                 email notifications. Actions are typically specified as
                 web interactions, for example, to fill and submit a
                 form with attributes of the triggering event. Our
                 evaluation shows that P eaCE's processing is dominated
                 by the time needed for accessing the web to extract
                 events and perform actions, allotting to 97.4\%. Thus,
                 PeaCE requires only 2.6\% overhead, and therefore, the
                 complex event processor scales well even with moderate
                 resources. We further show that simple and reasonable
                 restrictions on complex event specifications and the
                 timing of constituent events suffice to guarantee that
                 PeaCE only requires a constant buffer to process
                 arbitrarily many event announcements.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "16",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Cranor:2016:LSE,
  author =       "Lorrie Faith Cranor and Pedro Giovanni Leon and Blase
                 Ur",
  title =        "A Large-Scale Evaluation of {U.S.} Financial
                 Institutions' Standardized Privacy Notices",
  journal =      j-TWEB,
  volume =       "10",
  number =       "3",
  pages =        "17:1--17:??",
  month =        aug,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2911988",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 3 11:10:09 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Financial institutions in the United States are
                 required by the Gramm-Leach-Bliley Act to provide
                 annual privacy notices. In 2009, eight federal agencies
                 jointly released a model privacy form for these
                 disclosures. While the use of this model privacy form
                 is not required, it has been widely adopted. We
                 automatically evaluated 6,191 U.S. financial
                 institutions' privacy notices posted on the World Wide
                 Web. We found large variance in stated practices, even
                 among institutions of the same type. While thousands of
                 financial institutions share personal information
                 without providing the opportunity for consumers to opt
                 out, some institutions' practices are more privacy
                 protective. Regression analyses show that large
                 institutions and those headquartered in the
                 northeastern region share consumers' personal
                 information at higher rates than all other
                 institutions. Furthermore, our analysis helped us
                 uncover institutions that do not let consumers limit
                 data sharing when legally required to do so, as well as
                 institutions making self-contradictory statements. We
                 discuss implications for privacy in the financial
                 industry, issues with the design and use of the model
                 privacy form on the World Wide Web, and future
                 directions for standardized privacy notice.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "17",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Srba:2016:CSC,
  author =       "Ivan Srba and Maria Bielikova",
  title =        "A Comprehensive Survey and Classification of
                 Approaches for Community Question Answering",
  journal =      j-TWEB,
  volume =       "10",
  number =       "3",
  pages =        "18:1--18:??",
  month =        aug,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2934687",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 3 11:10:09 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Community question-answering (CQA) systems, such as
                 Yahoo! Answers or Stack Overflow, belong to a prominent
                 group of successful and popular Web 2.0 applications,
                 which are used every day by millions of users to find
                 an answer on complex, subjective, or context-dependent
                 questions. In order to obtain answers effectively, CQA
                 systems should optimally harness collective
                 intelligence of the whole online community, which will
                 be impossible without appropriate collaboration support
                 provided by information technologies. Therefore, CQA
                 became an interesting and promising subject of research
                 in computer science and now we can gather the results
                 of 10 years of research. Nevertheless, in spite of the
                 increasing number of publications emerging each year,
                 so far the research on CQA systems has missed a
                 comprehensive state-of-the-art survey. We attempt to
                 fill this gap by a review of 265 articles published
                 between 2005 and 2014, which were selected from major
                 conferences and journals. According to this evaluation,
                 at first we propose a framework that defines
                 descriptive attributes of CQA approaches. Second, we
                 introduce a classification of all approaches with
                 respect to problems they are aimed to solve. The
                 classification is consequently employed in a review of
                 a significant number of representative approaches,
                 which are described by means of attributes from the
                 descriptive framework. As a part of the survey, we also
                 depict the current trends as well as highlight the
                 areas that require further attention from the research
                 community.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "18",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Hwang:2016:PPS,
  author =       "Seung-Won Hwang and Saehoon Kim and Yuxiong He and
                 Sameh Elnikety and Seungjin Choi",
  title =        "Prediction and Predictability for Search Query
                 Acceleration",
  journal =      j-TWEB,
  volume =       "10",
  number =       "3",
  pages =        "19:1--19:??",
  month =        aug,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2943784",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 3 11:10:09 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "A commercial web search engine shards its index among
                 many servers, and therefore the response time of a
                 search query is dominated by the slowest server that
                 processes the query. Prior approaches target improving
                 responsiveness by reducing the tail latency, or
                 high-percentile response time, of an individual search
                 server. They predict query execution time, and if a
                 query is predicted to be long-running, it runs in
                 parallel; otherwise, it runs sequentially. These
                 approaches are, however, not accurate enough for
                 reducing a high tail latency when responses are
                 aggregated from many servers because this requires each
                 server to reduce a substantially higher tail latency
                 (e.g., the 99.99th percentile), which we call extreme
                 tail latency. To address tighter requirements of
                 extreme tail latency, we propose a new design space for
                 the problem, subsuming existing work and also proposing
                 a new solution space. Existing work makes a prediction
                 using features available at indexing time and focuses
                 on optimizing prediction features for accelerating tail
                 queries. In contrast, we identify ``when to predict?''
                 as another key optimization question. This opens up a
                 new solution of delaying a prediction by a short
                 duration to allow many short-running queries to
                 complete without parallelization and, at the same time,
                 to allow the predictor to collect a set of dynamic
                 features using runtime information. This new question
                 expands a solution space in two meaningful ways. First,
                 we see a significant reduction of tail latency by
                 leveraging ``dynamic'' features collected at runtime
                 that estimate query execution time with higher
                 accuracy. Second, we can ask whether to override
                 prediction when the ``predictability'' is low. We show
                 that considering predictability accelerates the query
                 by achieving a higher recall. With this prediction, we
                 propose to accelerate the queries that are predicted to
                 be long-running. In our preliminary work, we focused on
                 parallelization as an acceleration scenario. We extend
                 to consider heterogeneous multicore hardware for
                 acceleration. This hardware combines processor cores
                 with different microarchitectures such as
                 energy-efficient little cores and high-performance big
                 cores, and accelerating web search using this hardware
                 has remained an open problem. We evaluate the proposed
                 prediction framework in two scenarios: (1) query
                 parallelization on a multicore processor and (2) query
                 scheduling on a heterogeneous processor. Our extensive
                 evaluation results show that, for both scenarios of
                 query acceleration using parallelization and
                 heterogeneous cores, the proposed framework is
                 effective in reducing the extreme tail latency compared
                 to a start-of-the-art predictor because of its higher
                 recall, and it improves server throughput by more than
                 70\% because of its improved precision.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "19",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Eraslan:2016:STA,
  author =       "Sukru Eraslan and Yeliz Yesilada and Simon Harper",
  title =        "Scanpath Trend Analysis on {Web} Pages: Clustering Eye
                 Tracking Scanpaths",
  journal =      j-TWEB,
  volume =       "10",
  number =       "4",
  pages =        "20:1--20:??",
  month =        dec,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2970818",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 3 11:10:10 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Eye tracking studies have widely been used in
                 improving the design and usability of web pages and in
                 the research of understanding how users navigate them.
                 However, there is limited research in clustering users'
                 eye movement sequences (i.e., scanpaths) on web pages
                 to identify a general direction they follow. Existing
                 research tends to be reductionist, which means that the
                 resulting path is so short that it is not useful.
                 Moreover, there is little work on correlating users'
                 scanpaths with visual elements of web pages and the
                 underlying source code, which means the result cannot
                 be used for further processing. In order to address
                 these limitations, we introduce a new concept in
                 clustering scanpaths called Scanpath Trend Analysis
                 (STA) that not only considers the visual elements
                 visited by all users, but also considers the visual
                 elements visited by the majority in any order. We
                 present an algorithm which automatically does this
                 trend analysis to identify a trending scanpath for
                 multiple web users in terms of visual elements of a web
                 page. In contrast to existing research, the STA
                 algorithm first analyzes the most visited visual
                 elements in given scanpaths, clusters the scanpaths by
                 arranging these visual elements based on their overall
                 positions in the individual scanpaths, and then
                 constructs a trending scanpath in terms of these visual
                 elements. This algorithm was experimentally evaluated
                 by an eye tracking study on six web pages for two
                 different kinds of tasks (12 cases in total). Our
                 experimental results show that the STA algorithm
                 generates a trending scanpath that addresses the
                 reductionist problem of existing work by preventing the
                 loss of commonly visited visual elements for all cases.
                 Based on the statistical tests, the STA algorithm also
                 generates a trending scanpath that is significantly
                 more similar to the inputted scanpaths compared to
                 other existing work in 10 out of 12 cases. In the
                 remaining cases, the STA algorithm still performs
                 significantly better than some other existing work.
                 This algorithm contributes to behavior analysis
                 research on the web that can be used for different
                 purposes: for example, re-engineering web pages guided
                 by the trending scanpath to improve users' experience
                 or guiding designers to improve their design.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "20",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Rafalak:2016:WCC,
  author =       "Maria Rafalak and Dominik Deja and Adam Wierzbicki and
                 Radoslaw Nielek and Michal Kakol",
  title =        "{Web} Content Classification Using Distributions of
                 Subjective Quality Evaluations",
  journal =      j-TWEB,
  volume =       "10",
  number =       "4",
  pages =        "21:1--21:??",
  month =        dec,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2994132",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 3 11:10:10 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Machine learning algorithms and recommender systems
                 trained on human ratings are widely in use today.
                 However, human ratings may be associated with a high
                 level of uncertainty and are subjective, influenced by
                 demographic or psychological factors. We propose a new
                 approach to the design of object classes from human
                 ratings: the use of entire distributions to construct
                 classes. By avoiding aggregation for class definition,
                 our approach loses no information and can deal with
                 highly volatile or conflicting ratings. The approach is
                 based the concept of the Earth Mover's Distance (EMD),
                 a measure of distance for distributions. We evaluate
                 the proposed approach based on four datasets obtained
                 from diverse Web content or movie quality evaluation
                 services or experiments. We show that clusters
                 discovered in these datasets using the EMD measure are
                 characterized by a consistent and simple
                 interpretation. Quality classes defined using entire
                 rating distributions can be fitted to clusters of
                 distributions in the four datasets using two
                 parameters, resulting in a good overall fit. We also
                 consider the impact of the composition of small samples
                 on the distributions that are the basis of our
                 classification approach. We show that using
                 distributions based on small samples of 10 evaluations
                 is still robust to several demographic and
                 psychological variables. This observation suggests that
                 the proposed approach can be used in practice for
                 quality evaluation, even for highly uncertain and
                 subjective ratings.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "21",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Guo:2016:FEE,
  author =       "Guangming Guo and Feida Zhu and Enhong Chen and Qi Liu
                 and Le Wu and Chu Guan",
  title =        "From Footprint to Evidence: an Exploratory Study of
                 Mining Social Data for Credit Scoring",
  journal =      j-TWEB,
  volume =       "10",
  number =       "4",
  pages =        "22:1--22:??",
  month =        dec,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2996465",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 3 11:10:10 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "With the booming popularity of online social networks
                 like Twitter and Weibo, online user footprints are
                 accumulating rapidly on the social web. Simultaneously,
                 the question of how to leverage the large-scale
                 user-generated social media data for personal credit
                 scoring comes into the sight of both researchers and
                 practitioners. It has also become a topic of great
                 importance and growing interest in the P2P lending
                 industry. However, compared with traditional financial
                 data, heterogeneous social data presents both
                 opportunities and challenges for personal credit
                 scoring. In this article, we seek a deep understanding
                 of how to learn users' credit labels from social data
                 in a comprehensive and efficient way. Particularly, we
                 explore the social-data-based credit scoring problem
                 under the micro-blogging setting for its open, simple,
                 and real-time nature. To identify credit-related
                 evidence hidden in social data, we choose to conduct an
                 analytical and empirical study on a large-scale dataset
                 from Weibo, the largest and most popular tweet-style
                 website in China. Summarizing results from existing
                 credit scoring literature, we first propose three
                 social-data-based credit scoring principles as
                 guidelines for in-depth exploration. In addition, we
                 glean six credit-related insights arising from
                 empirical observations of the testbed dataset. Based on
                 the proposed principles and insights, we extract
                 prediction features mainly from three categories of
                 users' social data, including demographics, tweets, and
                 networks. To harness this broad range of features, we
                 put forward a two-tier stacking and boosting enhanced
                 ensemble learning framework. Quantitative investigation
                 of the extracted features shows that online social
                 media data does have good potential in discriminating
                 good credit users from bad. Furthermore, we perform
                 experiments on the real-world Weibo dataset consisting
                 of more than 7.3 million tweets and 200,000 users whose
                 credit labels are known through our third-party
                 partner. Experimental results show that (i) our
                 approach achieves a roughly 0.625 AUC value with all
                 the proposed social features as input, and (ii) our
                 learning algorithm can outperform traditional credit
                 scoring methods by as much as 17\% for
                 social-data-based personal credit scoring.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "22",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Bahri:2016:CCO,
  author =       "Leila Bahri and Barbara Carminati and Elena Ferrari",
  title =        "{COIP}-Continuous, Operable, Impartial, and
                 Privacy-Aware Identity Validity Estimation for {OSN}
                 Profiles",
  journal =      j-TWEB,
  volume =       "10",
  number =       "4",
  pages =        "23:1--23:??",
  month =        dec,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3014338",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 3 11:10:10 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Identity validation of Online Social Networks' (OSNs')
                 peers is a critical concern to the insurance of safe
                 and secure online socializing environments. Starting
                 from the vision of empowering users to determine the
                 validity of OSN identities, we suggest a framework to
                 estimate the trustworthiness of online social profiles
                 based only on the information they contain. Our
                 framework is based on learning identity correlations
                 between profile attributes in an OSN community and on
                 collecting ratings from OSN community members to
                 evaluate the trustworthiness of target profiles. Our
                 system guarantees utility, user anonymity, impartiality
                 in rating, and operability within the dynamics and
                 continuous evolution of OSNs. In this article, we
                 detail the system design, and we prove its correctness
                 against these claimed quality properties. Moreover, we
                 test its effectiveness, feasibility, and efficiency
                 through experimentation on real-world datasets from
                 Facebook and Google+, in addition to using the Adults
                 UCI dataset.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "23",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Das:2016:MAA,
  author =       "Sanmay Das and Allen Lavoie and Malik Magdon-Ismail",
  title =        "Manipulation among the Arbiters of Collective
                 Intelligence: How {Wikipedia} Administrators Mold
                 Public Opinion",
  journal =      j-TWEB,
  volume =       "10",
  number =       "4",
  pages =        "24:1--24:??",
  month =        dec,
  year =         "2016",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3001937",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 3 11:10:10 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Our reliance on networked, collectively built
                 information is a vulnerability when the quality or
                 reliability of this information is poor. Wikipedia, one
                 such collectively built information source, is often
                 our first stop for information on all kinds of topics;
                 its quality has stood up to many tests, and it prides
                 itself on having a ``neutral point of view.''
                 Enforcement of neutrality is in the hands of
                 comparatively few, powerful administrators. In this
                 article, we document that a surprisingly large number
                 of editors change their behavior and begin focusing
                 more on a particular controversial topic once they are
                 promoted to administrator status. The conscious and
                 unconscious biases of these few, but powerful,
                 administrators may be shaping the information on many
                 of the most sensitive topics on Wikipedia; some may
                 even be explicitly infiltrating the ranks of
                 administrators in order to promote their own points of
                 view. In addition, we ask whether administrators who
                 change their behavior in this suspicious manner can be
                 identified in advance. Neither prior history nor vote
                 counts during an administrator's election are useful in
                 doing so, but we find that an alternative measure,
                 which gives more weight to influential voters, can
                 successfully reject these suspicious candidates. This
                 second result has important implications for how we
                 harness collective intelligence: even if wisdom exists
                 in a collective opinion (like a vote), that signal can
                 be lost unless we carefully distinguish the true expert
                 voter from the noisy or manipulative voter.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "24",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Mukherjee:2017:ISV,
  author =       "Partha Mukherjee and Bernard J. Jansen",
  title =        "Information Sharing by Viewers Via Second Screens for
                 In-Real-Life Events",
  journal =      j-TWEB,
  volume =       "11",
  number =       "1",
  pages =        "1:1--1:??",
  month =        mar,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3009970",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 3 11:10:10 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The use of second screen devices with social media
                 facilitates conversational interaction concerning
                 broadcast media events, creating what we refer to as
                 the social soundtrack. In this research, we evaluate
                 the change of the Super Bowl XLIX social soundtrack
                 across three social media platforms on the topical
                 categories of commercials, music, and game at three
                 game phases ( Pre, During, and Post ). We perform
                 statistical analysis on more than 3M, 800K, and 50K
                 posts from Twitter, Instagram, and Tumblr,
                 respectively. Findings show that the volume of posts in
                 the During phase is fewer compared to Pre and Post
                 phases; however, the hourly mean in the During phase is
                 considerably higher than it is in the other two phases.
                 We identify the predominant phase and category of
                 interaction across all three social media sites. We
                 also determine the significance of change in absolute
                 scale across the Super Bowl categories (commercials,
                 music, game) and in both absolute and relative scales
                 across Super Bowl phases ( Pre, During, Post ) for the
                 three social network platforms (Twitter, Tumblr,
                 Instagram). Results show that significant
                 phase-category relationships exist for all three social
                 networks. The results identify the During phase as the
                 predominant one for all three categories on all social
                 media sites with respect to the absolute volume of
                 conversations in a continuous scale. From the relative
                 volume perspective, the During phase is highest for the
                 music category for most social networks. For the
                 commercials and game categories, however, the Post
                 phase is higher than the During phase for Twitter and
                 Instagram, respectively. Regarding category
                 identification, the game category is the highest for
                 Twitter and Instagram but not for Tumblr, which has
                 dominant peaks for music and/or commercials in all
                 three phases. It is apparent that different social
                 media platforms offer various phase and category
                 affordances. These results are important in identifying
                 the influence that second screen technology has on
                 information sharing across different social media
                 platforms and indicates that the viewer role is
                 transitioning from passive to more active.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "1",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Squicciarini:2017:TAO,
  author =       "Anna Squicciarini and Cornelia Caragea and Rahul
                 Balakavi",
  title =        "Toward Automated Online Photo Privacy",
  journal =      j-TWEB,
  volume =       "11",
  number =       "1",
  pages =        "2:1--2:??",
  month =        mar,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2983644",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 3 11:10:10 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Online photo sharing is an increasingly popular
                 activity for Internet users. More and more users are
                 now constantly sharing their images in various social
                 media, from social networking sites to online
                 communities, blogs, and content sharing sites. In this
                 article, we present an extensive study exploring
                 privacy and sharing needs of users' uploaded images. We
                 develop learning models to estimate adequate privacy
                 settings for newly uploaded images, based on carefully
                 selected image-specific features. Our study
                 investigates both visual and textual features of images
                 for privacy classification. We consider both basic
                 image-specific features, commonly used for image
                 processing, as well as more sophisticated and abstract
                 visual features. Additionally, we include a visual
                 representation of the sentiment evoked by images. To
                 our knowledge, sentiment has never been used in the
                 context of image classification for privacy purposes.
                 We identify the smallest set of features, that by
                 themselves or combined together with others, can
                 perform well in properly predicting the degree of
                 sensitivity of users' images. We consider both the case
                 of binary privacy settings (i.e., public, private), as
                 well as the case of more complex privacy options,
                 characterized by multiple sharing options. Our results
                 show that with few carefully selected features, one may
                 achieve high accuracy, especially when high-quality
                 tags are available.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "2",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Kang:2017:EMA,
  author =       "Jeon-Hyung Kang and Kristina Lerman",
  title =        "Effort Mediates Access to Information in Online Social
                 Networks",
  journal =      j-TWEB,
  volume =       "11",
  number =       "1",
  pages =        "3:1--3:??",
  month =        mar,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2990506",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 3 11:10:10 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Individuals' access to information in a social network
                 depends on how it is distributed and where in the
                 network individuals position themselves. In addition,
                 individuals vary in how much effort they invest in
                 managing their social connections. Using data from a
                 social media site, we study how the interplay between
                 effort and network position affects social media users'
                 access to diverse and novel information. Previous
                 studies of the role of networks in information access
                 were limited in their ability to measure the diversity
                 of information. We address this problem by learning the
                 topics of interest to social media users from the
                 messages they share online with followers. We use the
                 learned topics to measure the diversity of information
                 users receive from the people they follow online. We
                 confirm that users in structurally diverse network
                 positions, which bridge otherwise disconnected regions
                 of the follower network, tend to be exposed to more
                 diverse and novel information. We also show that users
                 who invest more effort in their activity on the site
                 are not only located in more structurally diverse
                 positions within the network than the less engaged
                 users but also receive more novel and diverse
                 information when in similar network positions. These
                 findings indicate that the relationship between network
                 structure and access to information in networks is more
                 nuanced than previously thought.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "3",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Seneviratne:2017:SMA,
  author =       "Suranga Seneviratne and Aruna Seneviratne and Mohamed
                 Ali Kaafar and Anirban Mahanti and Prasant Mohapatra",
  title =        "Spam Mobile Apps: Characteristics, Detection, and in
                 the Wild Analysis",
  journal =      j-TWEB,
  volume =       "11",
  number =       "1",
  pages =        "4:1--4:??",
  month =        mar,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3007901",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 3 11:10:10 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The increased popularity of smartphones has attracted
                 a large number of developers to offer various
                 applications for the different smartphone platforms via
                 the respective app markets. One consequence of this
                 popularity is that the app markets are also becoming
                 populated with spam apps. These spam apps reduce the
                 users' quality of experience and increase the workload
                 of app market operators to identify these apps and
                 remove them. Spam apps can come in many forms such as
                 apps not having a specific functionality, those having
                 unrelated app descriptions or unrelated keywords, or
                 similar apps being made available several times and
                 across diverse categories. Market operators maintain
                 antispam policies and apps are removed through
                 continuous monitoring. Through a systematic crawl of a
                 popular app market and by identifying apps that were
                 removed over a period of time, we propose a method to
                 detect spam apps solely using app metadata available at
                 the time of publication. We first propose a methodology
                 to manually label a sample of removed apps, according
                 to a set of checkpoint heuristics that reveal the
                 reasons behind removal. This analysis suggests that
                 approximately 35\% of the apps being removed are very
                 likely to be spam apps. We then map the identified
                 heuristics to several quantifiable features and show
                 how distinguishing these features are for spam apps. We
                 build an Adaptive Boost classifier for early
                 identification of spam apps using only the metadata of
                 the apps. Our classifier achieves an accuracy of over
                 95\% with precision varying between 85\% and 95\% and
                 recall varying between 38\% and 98\%. We further show
                 that a limited number of features, in the range of
                 10--30, generated from app metadata is sufficient to
                 achieve a satisfactory level of performance. On a set
                 of 180,627 apps that were present at the app market
                 during our crawl, our classifier predicts 2.7\% of the
                 apps as potential spam. Finally, we perform additional
                 manual verification and show that human reviewers agree
                 with 82\% of our classifier predictions.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "4",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Uribe:2017:UWP,
  author =       "Silvia Uribe and Federico {\'A}lvarez and Jos{\'e}
                 Manuel Men{\'e}ndez",
  title =        "User's {Web} Page Aesthetics Opinion: a Matter of
                 Low-Level Image Descriptors Based on {MPEG-7}",
  journal =      j-TWEB,
  volume =       "11",
  number =       "1",
  pages =        "5:1--5:??",
  month =        mar,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3019595",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 3 11:10:10 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Analyzing a user's first impression of a Web site is
                 essential for interface designers, as it is tightly
                 related to their overall opinion of a site. In fact,
                 this early evaluation affects user navigation behavior.
                 Perceived usability and user interest (e.g., revisiting
                 and recommending the site) are parameters influenced by
                 first opinions. Thus, predicting the latter when
                 creating a Web site is vital to ensure users'
                 acceptance. In this regard, Web aesthetics is one of
                 the most influential factors in this early perception.
                 We propose the use of low-level image parameters for
                 modeling Web aesthetics in an objective manner, which
                 is an innovative research field. Our model, obtained by
                 applying a stepwise multiple regression algorithm,
                 infers a user's first impression by analyzing three
                 different visual characteristics of Web site
                 screenshots-texture, luminance, and color-which are
                 directly derived from MPEG-7 descriptors. The results
                 obtained over three wide Web site datasets (composed by
                 415, 42, and 6 Web sites, respectively) reveal a high
                 correlation between low-level parameters and the users'
                 evaluation, thus allowing a more precise and objective
                 prediction of users' opinion than previous models that
                 are based on other image characteristics with fewer
                 predictors. Therefore, our model is meant to support a
                 rapid assessment of Web sites in early stages of the
                 design process to maximize the likelihood of the users'
                 final approval.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "5",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Parra-Arnau:2017:MBT,
  author =       "Javier Parra-Arnau and Jagdish Prasad Achara and
                 Claude Castelluccia",
  title =        "{MyAdChoices}: Bringing Transparency and Control to
                 Online Advertising",
  journal =      j-TWEB,
  volume =       "11",
  number =       "1",
  pages =        "7:1--7:??",
  month =        mar,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2996466",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 3 11:10:10 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The intrusiveness and the increasing invasiveness of
                 online advertising have, in the last few years, raised
                 serious concerns regarding user privacy and Web
                 usability. As a reaction to these concerns, we have
                 witnessed the emergence of a myriad of ad-blocking and
                 antitracking tools, whose aim is to return control to
                 users over advertising. The problem with these
                 technologies, however, is that they are extremely
                 limited and radical in their approach: users can only
                 choose either to block or allow all ads. With around
                 200 million people regularly using these tools, the
                 economic model of the Web-in which users get content
                 free in return for allowing advertisers to show them
                 ads-is at serious peril. In this article, we propose a
                 smart Web technology that aims at bringing transparency
                 to online advertising, so that users can make an
                 informed and equitable decision regarding ad blocking.
                 The proposed technology is implemented as a Web-browser
                 extension and enables users to exert fine-grained
                 control over advertising, thus providing them with
                 certain guarantees in terms of privacy and browsing
                 experience, while preserving the Internet economic
                 model. Experimental results in a real environment
                 demonstrate the suitability and feasibility of our
                 approach, and provide preliminary findings on
                 behavioral targeting from real user browsing
                 profiles.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "7",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Wang:2017:VMC,
  author =       "Tianyi Wang and Gang Wang and Bolun Wang and Divya
                 Sambasivan and Zengbin Zhang and Xing Li and Haitao
                 Zheng and Ben Y. Zhao",
  title =        "Value and Misinformation in Collaborative Investing
                 Platforms",
  journal =      j-TWEB,
  volume =       "11",
  number =       "2",
  pages =        "8:1--8:??",
  month =        may,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3027487",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jul 13 14:33:38 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "It is often difficult to separate the highly capable
                 ``experts'' from the average worker in crowdsourced
                 systems. This is especially true for challenge
                 application domains that require extensive domain
                 knowledge. The problem of stock analysis is one such
                 domain, where even the highly paid, well-educated
                 domain experts are prone to make mistakes. As an
                 extremely challenging problem space, the ``wisdom of
                 the crowds'' property that many crowdsourced
                 applications rely on may not hold. In this article, we
                 study the problem of evaluating and identifying experts
                 in the context of SeekingAlpha and StockTwits, two
                 crowdsourced investment services that have recently
                 begun to encroach on a space dominated for decades by
                 large investment banks. We seek to understand the
                 quality and impact of content on collaborative
                 investment platforms, by empirically analyzing complete
                 datasets of SeekingAlpha articles (9 years) and
                 StockTwits messages (4 years). We develop sentiment
                 analysis tools and correlate contributed content to the
                 historical performance of relevant stocks. While
                 SeekingAlpha articles and StockTwits messages provide
                 minimal correlation to stock performance in aggregate,
                 a subset of experts contribute more valuable
                 (predictive) content. We show that these authors can be
                 easily identified by user interactions, and investments
                 based on their analysis significantly outperform
                 broader markets. This effectively shows that even in
                 challenging application domains, there is a secondary
                 or indirect wisdom of the crowds. Finally, we conduct a
                 user survey that sheds light on users' views of
                 SeekingAlpha content and stock manipulation. We also
                 devote efforts to identify potential manipulation of
                 stocks by detecting authors controlling multiple
                 identities.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "8",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Drutsa:2017:PUE,
  author =       "Alexey Drutsa and Gleb Gusev and Pavel Serdyukov",
  title =        "Periodicity in User Engagement with a Search Engine
                 and Its Application to Online Controlled Experiments",
  journal =      j-TWEB,
  volume =       "11",
  number =       "2",
  pages =        "9:1--9:??",
  month =        may,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2856822",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jul 13 14:33:38 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Nowadays, billions of people use the Web in connection
                 with their daily needs. A significant part of these
                 needs are constituted by search tasks that are usually
                 addressed by search engines. Thus, daily search needs
                 result in regular user engagement with a search engine.
                 User engagement with web services was studied in
                 various aspects, but there appears to be little work
                 devoted to its regularity and periodicity. In this
                 article, we study periodicity of user engagement with a
                 popular search engine through applying spectrum
                 analysis to temporal sequences of different engagement
                 metrics. First, we found periodicity patterns of user
                 engagement and revealed classes of users whose
                 periodicity patterns do not change over a long period
                 of time. In addition, we give an exhaustive analysis of
                 the stability and quality of identified clusters.
                 Second, we used the spectrum series as key metrics to
                 evaluate search quality. We found that the novel
                 periodicity metrics outperform the state-of-the-art
                 quality metrics both in terms of significance level ( p
                 -value) and sensitivity to a large set of larges-scale
                 A/B experiments conducted on real search engine
                 users.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "9",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Rahman:2017:AAC,
  author =       "M. Rezaur Rahman and Jinyoung Han and Yong Jae Lee and
                 Chen-Nee Chuah",
  title =        "Analyzing the Adoption and Cascading Process of
                 {OSN}-Based Gifting Applications: an Empirical Study",
  journal =      j-TWEB,
  volume =       "11",
  number =       "2",
  pages =        "10:1--10:??",
  month =        may,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3023871",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jul 13 14:33:38 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "To achieve growth in the user base of online social
                 networks--(OSN) based applications, word-of-mouth
                 diffusion mechanisms, such as user-to-user invitations,
                 are widely used. This article characterizes the
                 adoption and cascading process of OSN-based
                 applications that grow via user invitations. We analyze
                 a detailed large-scale dataset of a popular Facebook
                 gifting application, iHeart, that contains more than 2
                 billion entries of user activities generated by 190
                 million users during a span of 64 weeks. We investigate
                 (1) how users invite their friends to an OSN-based
                 application, (2) how application adoption of an
                 individual user can be predicted, (3) what factors
                 drive the cascading process of application adoptions,
                 and (4) what are the good predictors of the ultimate
                 cascade sizes. We find that sending or receiving a
                 large number of invitations does not necessarily help
                 to recruit new users to iHeart. We also find that the
                 average success ratio of inviters is the most important
                 feature in predicting an adoption of an individual
                 user, which indicates that the effectiveness of
                 inviters has strong predictive power with respect to
                 application adoption. Based on the lessons learned from
                 our analyses, we build and evaluate learning-based
                 models to predict whether a user will adopt iHeart. Our
                 proposed model that utilizes additional activity
                 information of individual users from other similar
                 types of gifting applications can achieve high
                 precision (83\%) in predicting adoptions in the target
                 application (i.e., iHeart). We next identify a set of
                 distinctive features that are good predictors of the
                 growth of the application adoptions in terms of final
                 population size. We finally propose a prediction model
                 to infer whether a cascade of application adoption will
                 continue to grow in the future based on observing the
                 initial adoption process. Results show that our
                 proposed model can achieve high precision (over 80\%)
                 in predicting large cascades of application adoptions.
                 We believe our work can give an important implication
                 in resource allocation of OSN-based product
                 stakeholders, for example, via targeted marketing.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "10",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Matsubara:2017:NDI,
  author =       "Yasuko Matsubara and Yasushi Sakurai and B. Aditya
                 Prakash and Lei Li and Christos Faloutsos",
  title =        "Nonlinear Dynamics of Information Diffusion in Social
                 Networks",
  journal =      j-TWEB,
  volume =       "11",
  number =       "2",
  pages =        "11:1--11:??",
  month =        may,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3057741",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jul 13 14:33:38 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/string-matching.bib;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The recent explosion in the adoption of search engines
                 and new media such as blogs and Twitter have
                 facilitated the faster propagation of news and rumors.
                 How quickly does a piece of news spread over these
                 media? How does its popularity diminish over time? Does
                 the rising and falling pattern follow a simple
                 universal law? In this article, we propose SpikeM, a
                 concise yet flexible analytical model of the rise and
                 fall patterns of information diffusion. Our model has
                 the following advantages. First, unification power: it
                 explains earlier empirical observations and generalizes
                 theoretical models including the SI and SIR models. We
                 provide the threshold of the take-off versus die-out
                 conditions for SpikeM and discuss the generality of our
                 model by applying it to an arbitrary graph topology.
                 Second, practicality: it matches the observed behavior
                 of diverse sets of real data. Third, parsimony: it
                 requires only a handful of parameters. Fourth,
                 usefulness: it makes it possible to perform analytic
                 tasks such as forecasting, spotting anomalies, and
                 interpretation by reverse engineering the system
                 parameters of interest (quality of news, number of
                 interested bloggers, etc.). We also introduce an
                 efficient and effective algorithm for the real-time
                 monitoring of information diffusion, namely
                 SpikeStream, which identifies multiple diffusion
                 patterns in a large collection of online event streams.
                 Extensive experiments on real datasets demonstrate that
                 SpikeM accurately and succinctly describes all patterns
                 of the rise and fall spikes in social networks.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "11",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Rojas-Galeano:2017:OOO,
  author =       "Sergio Rojas-Galeano",
  title =        "On Obstructing Obscenity Obfuscation",
  journal =      j-TWEB,
  volume =       "11",
  number =       "2",
  pages =        "12:1--12:??",
  month =        may,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3032963",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jul 13 14:33:38 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Obscenity (the use of rude words or offensive
                 expressions) has spread from informal verbal
                 conversations to digital media, becoming increasingly
                 common on user-generated comments found in Web forums,
                 newspaper user boards, social networks, blogs, and
                 media-sharing sites. The basic obscenity-blocking
                 mechanism is based on verbatim comparisons against a
                 blacklist of banned vocabulary; however, creative users
                 circumvent these filters by obfuscating obscenity with
                 symbol substitutions or bogus segmentations that still
                 visually preserve the original semantics, such as
                 writing shit as {\em \$h`!t\/} or {\em s.h.i.t\/} or
                 even worse mixing them as {\em \$.h....`!.t\/}. The
                 number of potential obfuscated variants is
                 combinatorial, yielding the verbatim filter
                 impractical. Here we describe a method intended to
                 obstruct this anomaly inspired by sequence alignment
                 algorithms used in genomics, coupled with a tailor-made
                 edit penalty function. The method only requires to set
                 up the vocabulary of plain obscenities; no further
                 training is needed. Its complexity on screening a
                 single obscenity is linear, both in runtime and memory,
                 on the length of the user-generated text. We validated
                 the method on three different experiments. The first
                 one involves a new dataset that is also introduced in
                 this article; it consists of a set of manually
                 annotated real-life comments in Spanish, gathered from
                 the news user boards of an online newspaper, containing
                 this type of obfuscation. The second one is a publicly
                 available dataset of comments in Portuguese from a
                 sports Web site. In these experiments, at the obscenity
                 level, we observed recall rates greater than 90\%,
                 whereas precision rates varied between 75\% and 95\%,
                 depending on their sequence length (shorter lengths
                 yielded a higher number of false alarms). On the other
                 hand, at the comment level, we report recall of 86\%,
                 precision of 91\%, and specificity of 98\%. The last
                 experiment revealed that the method is more effective
                 in matching this type of obfuscation compared to the
                 classical Levenshtein edit distance. We conclude
                 discussing the prospects of the method to help
                 enforcing moderation rules of obscenity expressions or
                 as a preprocessing mechanism for sequence cleaning
                 and/or feature extraction in more sophisticated text
                 categorization techniques.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "12",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Xu:2017:EIE,
  author =       "Haitao Xu and Daiping Liu and Haining Wang and Angelos
                 Stavrou",
  title =        "An Empirical Investigation of
                 Ecommerce-Reputation-Escalation-as-a-Service",
  journal =      j-TWEB,
  volume =       "11",
  number =       "2",
  pages =        "13:1--13:??",
  month =        may,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2983646",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jul 13 14:33:38 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "In online markets, a store's reputation is closely
                 tied to its profitability. Sellers' desire to quickly
                 achieve a high reputation has fueled a profitable
                 underground business that operates as a specialized
                 crowdsourcing marketplace and accumulates wealth by
                 allowing online sellers to harness human laborers to
                 conduct fake transactions to improve their stores'
                 reputations. We term such an underground market a
                 seller-reputation-escalation (SRE) market. In this
                 article, we investigate the impact of the SRE service
                 on reputation escalation by performing in-depth
                 measurements of the prevalence of the SRE service, the
                 business model and market size of SRE markets, and the
                 characteristics of sellers and offered laborers. To
                 this end, we have infiltrated five SRE markets and
                 studied their operations using daily data collection
                 over a continuous period of 2 months. We identified
                 more than 11,000 online sellers posting at least
                 219,165 fake-purchase tasks on the five SRE markets.
                 These transactions earned at least \$46,438 in revenue
                 for the five SRE markets, and the total value of
                 merchandise involved exceeded \$3,452,530. Our study
                 demonstrates that online sellers using the SRE service
                 can increase their stores' reputations at least 10
                 times faster than legitimate ones while about 25\% of
                 them were visibly penalized. Even worse, we found a
                 much stealthier and more hazardous service that can,
                 within a single day, boost a seller's reputation by
                 such a degree that would require a legitimate seller at
                 least a year to accomplish. Armed with our analysis of
                 the operational characteristics of the underground
                 economy, we offer some insights into potential
                 mitigation strategies. Finally, we revisit the SRE
                 ecosystem 1 year later to evaluate the latest dynamism
                 of the SRE markets, especially the statuses of the
                 online stores once identified to launch
                 fake-transaction campaigns on the SRE markets. We
                 observe that the SRE markets are not as active as they
                 were 1 year ago and about 17\% of the involved online
                 stores become inaccessible likely because they have
                 been forcibly shut down by the corresponding E-commerce
                 marketplace for conducting fake transactions.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "13",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Singer:2017:BMC,
  author =       "Philipp Singer and Denis Helic and Andreas Hotho and
                 Markus Strohmaier",
  title =        "A {Bayesian} Method for Comparing Hypotheses About
                 Human Trails",
  journal =      j-TWEB,
  volume =       "11",
  number =       "3",
  pages =        "14:1--14:??",
  month =        jul,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3054950",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jul 13 14:33:39 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "When users interact with the Web today, they leave
                 sequential digital trails on a massive scale. Examples
                 of such human trails include Web navigation, sequences
                 of online restaurant reviews, or online music play
                 lists. Understanding the factors that drive the
                 production of these trails can be useful, for example,
                 for improving underlying network structures, predicting
                 user clicks, or enhancing recommendations. In this
                 work, we present a method called HypTrails for
                 comparing a set of hypotheses about human trails on the
                 Web, where hypotheses represent beliefs about
                 transitions between states. Our method utilizes Markov
                 chain models with Bayesian inference. The main idea is
                 to incorporate hypotheses as informative Dirichlet
                 priors and to calculate the evidence of the data under
                 them. For eliciting Dirichlet priors from hypotheses,
                 we present an adaption of the so-called (trial)
                 roulette method, and to compare the relative
                 plausibility of hypotheses, we employ Bayes factors. We
                 demonstrate the general mechanics and applicability of
                 HypTrails by performing experiments with (i) synthetic
                 trails for which we control the mechanisms that have
                 produced them and (ii) empirical trails stemming from
                 different domains including Web site navigation,
                 business reviews, and online music played. Our work
                 expands the repertoire of methods available for
                 studying human trails.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "14",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Vahedian:2017:MRH,
  author =       "Fatemeh Vahedian and Robin Burke and Bamshad
                 Mobasher",
  title =        "Multirelational Recommendation in Heterogeneous
                 Networks",
  journal =      j-TWEB,
  volume =       "11",
  number =       "3",
  pages =        "15:1--15:??",
  month =        jul,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3054952",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jul 13 14:33:39 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Recommender systems are key components in
                 information-seeking contexts where personalization is
                 sought. However, the dominant framework for
                 recommendation is essentially two dimensional, with the
                 interaction between users and items characterized by a
                 single relation. In many cases, such as social
                 networks, users and items are joined in a complex web
                 of relations, not readily reduced to a single value.
                 Recent multirelational approaches to recommendation
                 focus on the direct, proximal relations in which users
                 and items may participate. Our approach uses the
                 framework of complex heterogeneous networks to
                 represent such recommendation problems. We propose the
                 weighted hybrid of low-dimensional recommenders
                 (WHyLDR) recommendation model, which uses extended
                 relations, represented as constrained network paths, to
                 effectively augment direct relations. This model
                 incorporates influences from both distant and proximal
                 connections in the network. The WHyLDR approach raises
                 the problem of the unconstrained proliferation of
                 components, built from ever-extended network paths. We
                 show that although component utility is not strictly
                 monotonic with path length, a measure based on
                 information gain can effectively prune and optimize
                 such hybrids.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "15",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Sariyuce:2017:NDI,
  author =       "Ahmet Erdem Sariy{\"u}ce and C. Seshadhri and Ali
                 Pinar and {\"U}mit V. {\c{C}}ataly{\"u}rek",
  title =        "Nucleus Decompositions for Identifying Hierarchy of
                 Dense Subgraphs",
  journal =      j-TWEB,
  volume =       "11",
  number =       "3",
  pages =        "16:1--16:??",
  month =        jul,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3057742",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jul 13 14:33:39 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Finding dense substructures in a graph is a
                 fundamental graph mining operation, with applications
                 in bioinformatics, social networks, and visualization
                 to name a few. Yet most standard formulations of this
                 problem (like clique, quasi-clique, densest at-least- k
                 subgraph) are NP-hard. Furthermore, the goal is rarely
                 to find the ``true optimum'' but to identify many (if
                 not all) dense substructures, understand their
                 distribution in the graph, and ideally determine
                 relationships among them. Current dense subgraph
                 finding algorithms usually optimize some objective and
                 only find a few such subgraphs without providing any
                 structural relations. We define the nucleus
                 decomposition of a graph, which represents the graph as
                 a forest of nuclei. Each nucleus is a subgraph where
                 smaller cliques are present in many larger cliques. The
                 forest of nuclei is a hierarchy by containment, where
                 the edge density increases as we proceed towards leaf
                 nuclei. Sibling nuclei can have limited intersections,
                 which enables discovering overlapping dense
                 subgraphs. With the right parameters, the nucleus
                 decomposition generalizes the classic notions of
                 $k$-core and $k$-truss decompositions. We present
                 practical algorithms for nucleus decompositions and
                 empirically evaluate their behavior in a variety of
                 real graphs. The tree of nuclei consistently gives a
                 global, hierarchical snapshot of dense substructures
                 and outputs dense subgraphs of comparable quality with
                 the state-of-the-art solutions that are dense and have
                 non-trivial sizes. Our algorithms can process
                 real-world graphs with tens of millions of edges in
                 less than an hour. We demonstrate how proposed
                 algorithms can be utilized on a citation network. Our
                 analysis showed that dense units identified by our
                 algorithms correspond to coherent articles on a
                 specific area. Our experiments also show that we can
                 identify dense structures that are lost within larger
                 structures by other methods and find further finer
                 grain structure within dense groups.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "16",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Kanza:2017:LBD,
  author =       "Yaron Kanza and Elad Kravi and Eliyahu Safra and
                 Yehoshua Sagiv",
  title =        "Location-Based Distance Measures for Geosocial
                 Similarity",
  journal =      j-TWEB,
  volume =       "11",
  number =       "3",
  pages =        "17:1--17:??",
  month =        jul,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3054951",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jul 13 14:33:39 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "This article investigates the problem of geosocial
                 similarity among users of online social networks, based
                 on the locations of their activities (e.g., posting
                 messages or photographs). Finding pairs of geosocially
                 similar users or detecting that two sets of locations
                 (of activities) belong to the same user has important
                 applications in privacy protection, recommendation
                 systems, urban planning, and public health, among
                 others. It is explained and shown empirically that
                 common distance measures between sets of locations are
                 inadequate for determining geosocial similarity. Two
                 novel distance measures between sets of locations are
                 introduced. One is the mutually nearest distance that
                 is based on computing a matching between two sets. The
                 second measure uses a quad-tree index. It is highly
                 scalable but incurs the overhead of creating and
                 maintaining the index. Algorithms with optimization
                 techniques are developed for computing the two distance
                 measures and also for finding the $k$-most-similar
                 users of a given one. Extensive experiments, using
                 geotagged messages from Twitter, show that the new
                 distance measures are both more accurate and more
                 efficient than existing ones.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "17",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Panagopoulos:2017:MER,
  author =       "A. Panagopoulos and E. Koutrouli and A. Tsalgatidou",
  title =        "Modeling and Evaluating a Robust Feedback-Based
                 Reputation System for E-Commerce Platforms",
  journal =      j-TWEB,
  volume =       "11",
  number =       "3",
  pages =        "18:1--18:??",
  month =        jul,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3057265",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jul 13 14:33:39 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Despite the steady growth of e-commerce communities in
                 the past two decades, little has changed in the way
                 these communities manage reputation for building trust
                 and for protecting their member's financial interests
                 against fraud. As these communities mature and the
                 defects of their reputation systems are revealed,
                 further potential for deception against their members
                 is created, that pushes the need for novel reputation
                 mechanisms. Although a high volume of research works
                 has explored the concepts of reputation and trust in
                 e-communities, most of the proposed reputation systems
                 target decentralized e-communities, focusing on issues
                 related with the decentralized reputation management;
                 they have not thus been integrated in e-commerce
                 platforms. This work's objective is to provide an
                 attackresilient feedback-based reputation system for
                 modern e-commerce platforms, while minimizing the
                 incurred financial burden of potent security schemes.
                 Initially, we discuss a series of attacks and issues in
                 reputation systems and study the different approaches
                 of these problems from related works, while also
                 considering the structural properties, defense
                 mechanisms and policies of existing platforms. Then we
                 present our proposition for a robust reputation system
                 which consists of a novel reputation metric and attack
                 prevention mechanisms. Finally, we describe the
                 simulation framework and tool that we have implemented
                 for thoroughly testing and evaluating the metric's
                 resilience against attacks and present the evaluation
                 experiments and their results. We consider the
                 presented simulation framework as the second
                 contribution of our article, aiming at facilitating the
                 simulation and elaborate evaluation of reputation
                 systems which specifically target e-commerce platforms
                 by thoroughly presenting it, exhibiting its usage and
                 making it available to the research community.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "18",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Bianchini:2017:WMD,
  author =       "Devis Bianchini and Valeria {De Antonellis} and
                 Michele Melchiori",
  title =        "{WISeR}: a Multi-Dimensional Framework for Searching
                 and Ranking {Web APIs}",
  journal =      j-TWEB,
  volume =       "11",
  number =       "3",
  pages =        "19:1--19:??",
  month =        jul,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3061710",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jul 13 14:33:39 MDT 2017",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Mashups are agile applications that aggregate RESTful
                 services, developed by third parties, whose functions
                 are exposed as Web Application Program Interfaces
                 (APIs) within public repositories. From mashups
                 developers' viewpoint, Web API search may benefit from
                 selection criteria that combine several dimensions used
                 to describe the APIs, such as categories, tags, and
                 technical features (e.g., protocols and data formats).
                 Nevertheless, other dimensions might be fruitfully
                 exploited to support Web API search. Among them, past
                 API usage experiences by other developers may be used
                 to suggest the right APIs for a target application.
                 Past experiences might emerge from the co-occurrence of
                 Web APIs in the same mashups. Ratings assigned by
                 developers after using the Web APIs to create their own
                 mashups or after using mashups developed by others can
                 be considered as well. This article aims to advance the
                 current state of the art for Web API search and ranking
                 from mashups developers' point of view, by addressing
                 two key issues: multi-dimensional modeling and
                 multi-dimensional framework for selection. The model
                 for Web API characterization embraces multiple
                 descriptive dimensions, by considering several public
                 repositories, that focus on different and only
                 partially overlapping dimensions. The proposed Web API
                 selection framework, called WISeR (Web apI Search and
                 Ranking), is based on functions devoted to developers
                 to exploit the multi-dimensional descriptions, in order
                 to enhance the identification of candidate Web APIs to
                 be proposed, according to the given requirements.
                 Furthermore, WISeR adapts to changes that occur during
                 the Web API selection and mashup development, by
                 revising the dimensional attributes in order to conform
                 to developers' preferences and constraints. We also
                 present an experimental evaluation of the framework.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "19",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Rocha:2017:LPL,
  author =       "Andr{\'e} Rocha and C{\'a}ssio Prazeres",
  title =        "{LDoW--PaN}: Linked Data on the {Web}-Presentation and
                 Navigation",
  journal =      j-TWEB,
  volume =       "11",
  number =       "4",
  pages =        "20:1--20:??",
  month =        sep,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2983643",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Jan 15 08:22:45 MST 2018",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "This work aimed to propose LDoW-PaN, a Linked Data
                 presentation and navigation model focused on the
                 average user. The LDoW-PaN model is an extension of the
                 Dexter Hypertext Reference Model. Through the LDoW-PaN
                 model, ordinary people-who have no experience with
                 technologies that involve the Linked Data
                 environment-can interact with the Web of Data (RDF)
                 more closely related to how they interact with the Web
                 of Documents (HTML). To evaluate the proposal, some
                 tools were developed, including the following: (i) a
                 Web Service, which implements the lower-level layers of
                 the LDoW-PaN model; (ii) a client-side script library,
                 which implements the presentation and navigation layer;
                 and (iii) a browser extension, which uses these tools
                 to provide Linked Data presentation and navigation to
                 users browsing the Web. The browser extension was
                 developed using user interface approaches that are well
                 known, well accepted, and evaluated by the Web research
                 community, such as faceted navigation and presentation
                 through tooltips. Therefore, the prototype evaluation
                 included: usability evaluation through two classical
                 techniques; computational complexity measures; and an
                 analysis of the performance of the operations provided
                 by the proposed model.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "20",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Wang:2017:CUB,
  author =       "Gang Wang and Xinyi Zhang and Shiliang Tang and
                 Christo Wilson and Haitao Zheng and Ben Y. Zhao",
  title =        "Clickstream User Behavior Models",
  journal =      j-TWEB,
  volume =       "11",
  number =       "4",
  pages =        "21:1--21:??",
  month =        sep,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3068332",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Jan 15 08:22:45 MST 2018",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The next generation of Internet services is driven by
                 users and user-generated content. The complex nature of
                 user behavior makes it highly challenging to manage and
                 secure online services. On one hand, service providers
                 cannot effectively prevent attackers from creating
                 large numbers of fake identities to disseminate
                 unwanted content (e.g., spam). On the other hand,
                 abusive behavior from real users also poses significant
                 threats (e.g., cyberbullying). In this article, we
                 propose clickstream models to characterize user
                 behavior in large online services. By analyzing
                 clickstream traces (i.e., sequences of click events
                 from users), we seek to achieve two goals: (1)
                 detection: to capture distinct user groups for the
                 detection of malicious accounts, and (2) understanding:
                 to extract semantic information from user groups to
                 understand the captured behavior. To achieve these
                 goals, we build two related systems. The first one is a
                 semisupervised system to detect malicious user accounts
                 (Sybils). The core idea is to build a clickstream
                 similarity graph where each node is a user and an edge
                 captures the similarity of two users' clickstreams.
                 Based on this graph, we propose a coloring scheme to
                 identify groups of malicious accounts without relying
                 on a large labeled dataset. We validate the system
                 using ground-truth clickstream traces of 16,000 real
                 and Sybil users from Renren, a large Chinese social
                 network. The second system is an unsupervised system
                 that aims to capture and understand the fine-grained
                 user behavior. Instead of binary classification
                 (malicious or benign), this model identifies the
                 natural groups of user behavior and automatically
                 extracts features to interpret their semantic meanings.
                 Applying this system to Renren and another online
                 social network, Whisper (100K users), we help service
                 providers identify unexpected user behaviors and even
                 predict users' future actions. Both systems received
                 positive feedback from our industrial collaborators
                 including Renren, LinkedIn, and Whisper after testing
                 on their internal clickstream data.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "21",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Hogan:2017:CFI,
  author =       "Aidan Hogan",
  title =        "Canonical Forms for Isomorphic and Equivalent {RDF}
                 Graphs: Algorithms for Leaning and Labelling Blank
                 Nodes",
  journal =      j-TWEB,
  volume =       "11",
  number =       "4",
  pages =        "22:1--22:??",
  month =        sep,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3068333",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Jan 15 08:22:45 MST 2018",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Existential blank nodes greatly complicate a number of
                 fundamental operations on Resource Description
                 Framework (RDF) graphs. In particular, the problems of
                 determining if two RDF graphs have the same structure
                 modulo blank node labels (i.e., if they are isomorphic
                 ), or determining if two RDF graphs have the same
                 meaning under simple semantics (i.e., if they are
                 simple-equivalent ), have no known polynomial-time
                 algorithms. In this article, we propose methods that
                 can produce two canonical forms of an RDF graph. The
                 first canonical form preserves isomorphism such that
                 any two isomorphic RDF graphs will produce the same
                 canonical form; this iso-canonical form is produced by
                 modifying the well-known canonical labelling algorithm
                 N auty for application to RDF graphs. The second
                 canonical form additionally preserves
                 simple-equivalence such that any two simple-equivalent
                 RDF graphs will produce the same canonical form; this
                 equi-canonical form is produced by, in a preliminary
                 step, leaning the RDF graph, and then computing the
                 iso-canonical form. These algorithms have a number of
                 practical applications, such as for identifying
                 isomorphic or equivalent RDF graphs in a large
                 collection without requiring pairwise comparison, for
                 computing checksums or signing RDF graphs, for applying
                 consistent Skolemisation schemes where blank nodes are
                 mapped in a canonical manner to Internationalised
                 Resource Identifiers (IRIs), and so forth. Likewise a
                 variety of algorithms can be simplified by presupposing
                 RDF graphs in one of these canonical forms. Both
                 algorithms require exponential steps in the worst case;
                 in our evaluation we demonstrate that there indeed
                 exist difficult synthetic cases, but we also provide
                 results over 9.9 million RDF graphs that suggest such
                 cases occur infrequently in the real world, and that
                 both canonical forms can be efficiently computed in all
                 but a handful of such cases.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "22",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Koutrika:2017:SWP,
  author =       "Georgia Koutrika and Qian Lin",
  title =        "A Study of {Web} Print: What People Print in the
                 Digital Era",
  journal =      j-TWEB,
  volume =       "11",
  number =       "4",
  pages =        "23:1--23:??",
  month =        sep,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3068331",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Jan 15 08:22:45 MST 2018",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "This article analyzes a proprietary log of printed web
                 pages and aims at answering questions regarding the
                 content people print (what), the reasons they print
                 (why), as well as attributes of their print profile
                 (who). We present a classification of pages printed
                 based on their print intent and we describe our
                 methodology for processing the print dataset used in
                 this study. In our analysis, we study the web sites,
                 topics, and print intent of the pages printed along the
                 following aspects: popularity, trends, activity, user
                 diversity, and consistency. We present several findings
                 that reveal interesting insights into printing. We
                 analyze our findings and discuss their impact and
                 directions for future work.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "23",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Bernaschi:2017:EAT,
  author =       "Massimo Bernaschi and Alessandro Celestini and Stefano
                 Guarino and Flavio Lombardi",
  title =        "Exploring and Analyzing the {Tor} Hidden Services
                 Graph",
  journal =      j-TWEB,
  volume =       "11",
  number =       "4",
  pages =        "24:1--24:??",
  month =        sep,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3008662",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Jan 15 08:22:45 MST 2018",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The exploration and analysis of Web graphs has
                 flourished in the recent past, producing a large number
                 of relevant and interesting research results. However,
                 the unique characteristics of the Tor network limit the
                 applicability of standard techniques and demand for
                 specific algorithms to explore and analyze it. The
                 attention of the research community has focused on
                 assessing the security of the Tor infrastructure (i.e.,
                 its ability to actually provide the intended level of
                 anonymity) and on discussing what Tor is currently
                 being used for. Since there are no foolproof techniques
                 for automatically discovering Tor hidden services,
                 little or no information is available about the
                 topology of the Tor Web graph. Even less is known on
                 the relationship between content similarity and
                 topological structure. The present article aims at
                 addressing such lack of information. Among its
                 contributions: a study on automatic Tor Web
                 exploration/data collection approaches; the adoption of
                 novel representative metrics for evaluating Tor data; a
                 novel in-depth analysis of the hidden services graph; a
                 rich correlation analysis of hidden services' semantics
                 and topology. Finally, a broad interesting set of novel
                 insights/considerations over the Tor Web organization
                 and content are provided.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "24",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Xu:2017:COF,
  author =       "Chang Xu and Jie Zhang",
  title =        "Collusive Opinion Fraud Detection in Online Reviews: a
                 Probabilistic Modeling Approach",
  journal =      j-TWEB,
  volume =       "11",
  number =       "4",
  pages =        "25:1--25:??",
  month =        sep,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3098859",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Jan 15 08:22:45 MST 2018",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "We address the collusive opinion fraud problem in
                 online review portals, where groups of people work
                 together to deliver deceptive reviews for manipulating
                 the reputations of targeted items. Such collusive fraud
                 is considered much harder to defend against, since the
                 participants (or colluders) can evade detection by
                 shaping their behaviors collectively so as not to
                 appear suspicious. To alleviate this problem,
                 countermeasures have been proposed that leverage the
                 collective behaviors of colluders. The motivation stems
                 from the observation that colluders typically act in a
                 very synchronized way, as they are instructed by the
                 same campaigns with common items to target and
                 schedules to follow. However, the collective behaviors
                 examined in existing solutions focus mostly on the
                 external appearance of fraud campaigns, such as the
                 campaign size and the size of the targeted item set.
                 These signals may become ineffective once colluders
                 have changed their behaviors collectively. Moreover,
                 the detection algorithms used in existing approaches
                 are designed to only make collusion inference on the
                 input data; predictive models that can be deployed for
                 detecting emerging fraud cannot be learned from the
                 data. In this article, to complement existing studies
                 on collusive opinion fraud characterization and
                 detection, we explore more subtle behavioral trails in
                 collusive fraud practice. In particular, a suite of
                 homogeneity-based measures are proposed to capture the
                 interrelationships among colluders within campaigns.
                 Moreover, a novel statistical model is proposed to
                 further characterize, recognize, and predict collusive
                 fraud in online reviews. The proposed model is fully
                 unsupervised and highly flexible to incorporate
                 effective measures available for better modeling and
                 prediction. Through experiments on two real-world
                 datasets, we show that our method outperforms the state
                 of the art in both characterization and detection
                 abilities.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "25",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Chattopadhyay:2017:FSM,
  author =       "Soumi Chattopadhyay and Ansuman Banerjee and Nilanjan
                 Banerjee",
  title =        "A Fast and Scalable Mechanism for {Web} Service
                 Composition",
  journal =      j-TWEB,
  volume =       "11",
  number =       "4",
  pages =        "26:1--26:??",
  month =        sep,
  year =         "2017",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3098884",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Jan 15 08:22:45 MST 2018",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "In recent times, automated business processes and web
                 services have become ubiquitous in diverse application
                 spaces. Efficient composition of web services in real
                 time while providing necessary Quality of Service (QoS)
                 guarantees is a computationally complex problem and
                 several heuristic based approaches have been proposed
                 to compose the services optimally. In this article, we
                 present the design of a scalable QoS-aware service
                 composition mechanism that balances the computational
                 complexity of service composition with the QoS
                 guarantees of the composed service and achieves
                 scalability. Our design guarantees a single QoS
                 parameter using an intelligent search and pruning
                 mechanism in the composed service space. We also show
                 that our methodology yields near optimal solutions on
                 real benchmarks. We then enhance our proposed mechanism
                 to guarantee multiple QoS parameters using aggregation
                 techniques. Finally, we explore search time versus
                 solution quality tradeoff using parameterized search
                 algorithms that produce better-quality solutions at the
                 cost of delay. We present experimental results to show
                 the efficiency of our proposed mechanism.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "26",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{He:2018:EET,
  author =       "Ming He and Yong Ge and Enhong Chen and Qi Liu and
                 Xuesong Wang",
  title =        "Exploring the Emerging Type of Comment for Online
                 Videos: {DanMu}",
  journal =      j-TWEB,
  volume =       "12",
  number =       "1",
  pages =        "1:1--1:??",
  month =        feb,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3098885",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jun 28 14:10:00 MDT 2018",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "DanMu, an emerging type of user-generated comment, has
                 become increasingly popular in recent years. Many
                 online video platforms such as Tudou.com have provided
                 the DanMu function. Unlike traditional online reviews
                 such as reviews at Youtube.com that are outside the
                 videos, DanMu is a scrolling marquee comment, which is
                 overlaid directly on top of the video and synchronized
                 to a specific playback time. Such comments are
                 displayed as streams of moving subtitles overlaid on
                 the video screen. Viewers could easily write DanMu s
                 while watching videos, and the written DanMu s will be
                 immediately overlaid onto the video and displayed to
                 writers themselves and other viewers as well. Such
                 DanMu systems have greatly enabled users to communicate
                 with each other in a much more direct way, creating a
                 real-time sharing experience. Although there are
                 several unique features of DanMu and has had a great
                 impact on online video systems, to the best of our
                 knowledge, there is no work that has provided a
                 comprehensive study on DanMu. In this article, as a
                 pilot study, we analyze the unique characteristics of
                 DanMu from various perspectives. Specifically, we first
                 illustrate some unique distributions of DanMu s by
                 comparing with traditional reviews (TReviews) that we
                 collected from a real DanMu -enabled online video
                 system. Second, we discover two interesting patterns in
                 DanMu data: a herding effect and multiple-burst
                 phenomena that are significantly different from those
                 in TRviews and reveal important insights about the
                 growth of DanMu s on a video. Towards exploring
                 antecedents of both th herding effect and
                 multiple-burst phenomena, we propose to further detect
                 leading DanMu s within bursts, because those leading
                 DanMu s make the most contribution to both patterns. A
                 framework is proposed to detect leading DanMu s that
                 effectively combines multiple factors contributing to
                 leading DanMu s. Based on the identified
                 characteristics of DanMu, finally we propose to predict
                 the distribution of future DanMu s (i.e., the growth of
                 DanMu s), which is important for many DanMu -enabled
                 online video systems, for example, the predicted DanMu
                 distribution could be an indicator of video popularity.
                 This prediction task includes two aspects: One is to
                 predict which videos future DanMu s will be posted for,
                 and the other one is to predict which segments of a
                 video future DanMu s will be posted on. We develop two
                 sophisticated models to solve both problems. Finally,
                 intensive experiments are conducted with a real-world
                 dataset to validate all methods developed in this
                 article.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "1",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Minervini:2018:AKP,
  author =       "Pasquale Minervini and Volker Tresp and Claudia
                 D'amato and Nicola Fanizzi",
  title =        "Adaptive Knowledge Propagation in {Web} Ontologies",
  journal =      j-TWEB,
  volume =       "12",
  number =       "1",
  pages =        "2:1--2:??",
  month =        feb,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3105961",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jun 28 14:10:00 MDT 2018",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "We focus on the problem of predicting missing
                 assertions in Web ontologies. We start from the
                 assumption that individual resources that are similar
                 in some aspects are more likely to be linked by
                 specific relations: this phenomenon is also referred to
                 as homophily and emerges in a variety of relational
                 domains. In this article, we propose a method for (1)
                 identifying which relations in the ontology are more
                 likely to link similar individuals and (2) efficiently
                 propagating knowledge across chains of similar
                 individuals. By enforcing sparsity in the model
                 parameters, the proposed method is able to select only
                 the most relevant relations for a given prediction
                 task. Our experimental evaluation demonstrates the
                 effectiveness of the proposed method in comparison to
                 state-of-the-art methods from the literature.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "2",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Liu:2018:RCW,
  author =       "Yining Liu and Yong Liu and Yanming Shen and Keqiu
                 Li",
  title =        "Recommendation in a Changing World: Exploiting
                 Temporal Dynamics in Ratings and Reviews",
  journal =      j-TWEB,
  volume =       "12",
  number =       "1",
  pages =        "3:1--3:??",
  month =        feb,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3108238",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jun 28 14:10:00 MDT 2018",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Users' preferences, and consequently their ratings and
                 reviews to items, change over time. Likewise,
                 characteristics of items are also time-varying. By
                 dividing data into time periods, temporal Recommender
                 Systems (RSs) improve recommendation accuracy by
                 exploring the temporal dynamics in user rating data.
                 However, temporal RSs have to cope with rating sparsity
                 in each time period. Meanwhile, reviews generated by
                 users contain rich information about their preferences,
                 which can be exploited to address rating sparsity and
                 further improve the performance of temporal RSs. In
                 this article, we develop a temporal rating model with
                 topics that jointly mines the temporal dynamics of both
                 user-item ratings and reviews. Studying temporal drifts
                 in reviews helps us understand item rating evolutions
                 and user interest changes over time. Our model also
                 automatically splits the review text in each time
                 period into interim words and intrinsic words. By
                 linking interim words and intrinsic words to short-term
                 and long-term item features, respectively, we jointly
                 mine the temporal changes in user and item latent
                 features together with the associated review text in a
                 single learning stage. Through experiments on 28
                 real-world datasets collected from Amazon, we show that
                 the rating prediction accuracy of our model
                 significantly outperforms the existing state-of-art RS
                 models. And our model can automatically identify
                 representative interim words in each time period as
                 well as intrinsic words across all time periods. This
                 can be very useful in understanding the time evolution
                 of users' preferences and items' characteristics.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "3",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Tu:2018:ARP,
  author =       "Wenting Tu and David W. Cheung and Nikos Mamoulis and
                 Min Yang and Ziyu Lu",
  title =        "Activity Recommendation with Partners",
  journal =      j-TWEB,
  volume =       "12",
  number =       "1",
  pages =        "4:1--4:??",
  month =        feb,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3121407",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jun 28 14:10:00 MDT 2018",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Recommending social activities, such as watching
                 movies or having dinner, is a common function found in
                 social networks or e-commerce sites. Besides certain
                 websites which manage activity-related locations (e.g.,
                 foursquare.com), many items on product sale platforms
                 (e.g., groupon.com) can naturally be mapped to social
                 activities. For example, movie tickets can be thought
                 of as activity items, which can be mapped as a social
                 activity of ``watch a movie.'' Traditional recommender
                 systems estimate the degree of interest for a target
                 user on candidate items (or activities), and
                 accordingly, recommend the top-$k$ activity items to
                 the user. However, these systems ignore an important
                 social characteristic of recommended activities: people
                 usually tend to participate in those activities with
                 friends. This article considers this fact for improving
                 the effectiveness of recommendation in two directions.
                 First, we study the problem of activity-partner
                 recommendation; i.e., for each recommended activity
                 item, find a suitable partner for the user. This (i)
                 saves the user's time for finding activity partners,
                 (ii) increases the likelihood that the activity item
                 will be selected by the user, and (iii) improves the
                 effectiveness of recommender systems to users overall
                 and enkindles their social enthusiasm. Our partner
                 recommender is built upon the users' historical
                 attendance preferences, their social context, and
                 geographic information. Moreover, we explore how to
                 leverage the partner recommendation to help improve the
                 effectiveness of recommending activities to users.
                 Assuming that users tend to select the activities for
                 which they can find suitable partners, we propose a
                 partner-aware activity recommendation model, which
                 integrates this hypothesis into conventional
                 recommendation approaches. Finally, the recommended
                 items not only match users' interests, but also have
                 high chances to be selected by the users, because the
                 users can find suitable partners to attend the
                 corresponding activities together. We conduct
                 experiments on real data to evaluate the effectiveness
                 of activity-partner recommendation and partner-aware
                 activity recommendation. The results verify that (i)
                 suggesting partners greatly improves the likelihood
                 that a recommended activity item is to be selected by
                 the target user and (ii) considering the existence of
                 suitable partners in the ranking of recommended items
                 improves the accuracy of recommendation
                 significantly.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "4",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Dutta:2018:CRM,
  author =       "Kaushik Dutta and Debra Vandermeer",
  title =        "Caching to Reduce Mobile App Energy Consumption",
  journal =      j-TWEB,
  volume =       "12",
  number =       "1",
  pages =        "5:1--5:??",
  month =        feb,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3125778",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jun 28 14:10:00 MDT 2018",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Mobile applications consume device energy for their
                 operations, and the fast rate of battery depletion on
                 mobile devices poses a major usability hurdle. After
                 the display, data communication is the second-biggest
                 consumer of mobile device energy. At the same time,
                 software applications that run on mobile devices
                 represent a fast-growing product segment. Typically,
                 these applications serve as front-end display
                 mechanisms, which fetch data from remote servers and
                 display the information to the user in an appropriate
                 format-incurring significant data communication
                 overheads in the process. In this work, we propose
                 methods to reduce energy overheads in mobile devices
                 due to data communication by leveraging data caching
                 technology. A review of existing caching mechanisms
                 revealed that they are primarily designed for
                 optimizing response time performance and cannot be
                 easily ported to mobile devices for energy savings.
                 Further, architectural differences between traditional
                 client-server and mobile communications infrastructures
                 make the use of existing caching technologies
                 unsuitable in mobile devices. In this article, we
                 propose a set of two new caching approaches
                 specifically designed with the constraints of mobile
                 devices in mind: (a) a response caching approach and
                 (b) an object caching approach. Our experiments show
                 that, even for a small cache size of 250MB, object
                 caching can reduce energy consumption on average by
                 45\% compared to the no-cache case, and response
                 caching can reduce energy consumption by 20\% compared
                 to the no-cache case. The benefits increase with larger
                 cache sizes. These results demonstrate the efficacy of
                 our proposed method and raise the possibility of
                 significantly extending mobile device battery life.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "5",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Manta-Caro:2018:MSW,
  author =       "Cristyan Manta-Caro and Juan M. Fern{\'a}ndez-Luna",
  title =        "Modeling and Simulating the {Web of Things} from an
                 Information Retrieval Perspective",
  journal =      j-TWEB,
  volume =       "12",
  number =       "1",
  pages =        "6:1--6:??",
  month =        feb,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3132732",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jun 28 14:10:00 MDT 2018",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Internet and Web technologies have changed our lives
                 in ways we are not yet fully aware of. In the near
                 future, Internet will interconnect more than 50 billion
                 things in the real world, nodes will sense billions of
                 features and properties of interest, and things will be
                 represented by web-based, bi-directional services with
                 highly dynamic content and real-time data. This is the
                 new era of the Internet and the Web of Things. Since
                 the emergence of such paradigms implies the evolution
                 and integration of the systems with which they
                 interact, it is essential to develop abstract models
                 for representing and simulating the Web of Things in
                 order to establish new approaches. This article
                 describes a Web of Things model based on a structured
                 XML representation. We also present a simulator whose
                 ultimate goal is to encapsulate the expected dynamics
                 of the Web of Things for the future development of
                 information retrieval (IR) systems. The simulator
                 generates a real-time collection of XML documents
                 containing spatio-temporal contexts and textual and
                 sensed information of highly dynamic dimensions. The
                 simulator is characterized by its flexibility and
                 versatility for representing real-world scenarios and
                 offers a unique perspective for information retrieval.
                 In this article, we evaluate and test the simulator in
                 terms of its performance variables for computing
                 resource consumption and present our experimentation
                 with the simulator on three real scenarios by
                 considering the generation variables for the IR
                 document collection.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "6",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Davison:2018:LTR,
  author =       "Brian D. Davison",
  title =        "List of 2016 {TWEB} Reviewers",
  journal =      j-TWEB,
  volume =       "12",
  number =       "1",
  pages =        "7:1--7:??",
  month =        feb,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3180440",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jun 28 14:10:00 MDT 2018",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "7",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Davison:2018:E,
  author =       "Brian D. Davison",
  title =        "Editorial",
  journal =      j-TWEB,
  volume =       "12",
  number =       "2",
  pages =        "8:1--8:??",
  month =        jun,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3232925",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jun 28 14:10:01 MDT 2018",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "8e",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Jia:2018:KGE,
  author =       "Yantao Jia and Yuanzhuo Wang and Xiaolong Jin and
                 Hailun Lin and Xueqi Cheng",
  title =        "Knowledge Graph Embedding: a Locally and Temporally
                 Adaptive Translation-Based Approach",
  journal =      j-TWEB,
  volume =       "12",
  number =       "2",
  pages =        "8:1--8:??",
  month =        jun,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3132733",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jun 28 14:10:01 MDT 2018",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "A knowledge graph is a graph with entities of
                 different types as nodes and various relations among
                 them as edges. The construction of knowledge graphs in
                 the past decades facilitates many applications, such as
                 link prediction, web search analysis, question
                 answering, and so on. Knowledge graph embedding aims to
                 represent entities and relations in a large-scale
                 knowledge graph as elements in a continuous vector
                 space. Existing methods, for example, TransE, TransH,
                 and TransR, learn the embedding representation by
                 defining a global margin-based loss function over the
                 data. However, the loss function is determined during
                 experiments whose parameters are examined among a
                 closed set of candidates. Moreover, embeddings over two
                 knowledge graphs with different entities and relations
                 share the same set of candidates, ignoring the locality
                 of both graphs. This leads to the limited performance
                 of embedding related applications. In this article, a
                 locally adaptive translation method for knowledge graph
                 embedding, called TransA, is proposed to find the loss
                 function by adaptively determining its margin over
                 different knowledge graphs. Then the convergence of
                 TransA is verified from the aspect of its uniform
                 stability. To make the embedding methods up-to-date
                 when new vertices and edges are added into the
                 knowledge graph, the incremental algorithm for TransA,
                 called iTransA, is proposed by adaptively adjusting the
                 optimal margin over time. Experiments on four benchmark
                 data sets demonstrate the superiority of the proposed
                 method, as compared to the state-of-the-art ones.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "8",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Park:2018:WSD,
  author =       "Souneil Park and Aleksandar Matic and Kamini Garg and
                 Nuria Oliver",
  title =        "When Simpler Data Does Not Imply Less Information: a
                 Study of User Profiling Scenarios With Constrained View
                 of Mobile {HTTP(S)} Traffic",
  journal =      j-TWEB,
  volume =       "12",
  number =       "2",
  pages =        "9:1--9:??",
  month =        jun,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3143402",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jun 28 14:10:01 MDT 2018",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The exponential growth in smartphone adoption is
                 contributing to the availability of vast amounts of
                 human behavioral data. This data enables the
                 development of increasingly accurate data-driven user
                 models that facilitate the delivery of personalized
                 services that are often free in exchange for the use of
                 its customers' data. Although such usage conventions
                 have raised many privacy concerns, the increasing value
                 of personal data is motivating diverse entities to
                 aggressively collect and exploit the data. In this
                 article, we unfold profiling scenarios around mobile
                 HTTP(S) traffic, focusing on those that have limited
                 but meaningful segments of the data. The capability of
                 the scenarios to profile personal information is
                 examined with real user data, collected in the wild
                 from 61 mobile phone users for a minimum of 30 days.
                 Our study attempts to model heterogeneous user traits
                 and interests, including personality, boredom
                 proneness, demographics, and shopping interests. Based
                 on our modeling results, we discuss various
                 implications to personalization, privacy, and personal
                 data rights.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "9",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Calzavara:2018:SBA,
  author =       "Stefano Calzavara and Alvise Rabitti and Michele
                 Bugliesi",
  title =        "Semantics-Based Analysis of Content Security Policy
                 Deployment",
  journal =      j-TWEB,
  volume =       "12",
  number =       "2",
  pages =        "10:1--10:??",
  month =        jun,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3149408",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jun 28 14:10:01 MDT 2018",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Content Security Policy (CSP) is a recent W3C standard
                 introduced to prevent and mitigate the impact of
                 content injection vulnerabilities on websites. In this
                 article, we introduce a formal semantics for the latest
                 stable version of the standard, CSP Level 2. We then
                 perform a systematic, large-scale analysis of the
                 effectiveness of the current CSP deployment, using the
                 formal semantics to substantiate our methodology and to
                 assess the impact of the detected issues. We focus on
                 four key aspects that affect the effectiveness of CSP:
                 browser support, website adoption, correct
                 configuration, and constant maintenance. Our analysis
                 shows that browser support for CSP is largely
                 satisfactory, with the exception of a few notable
                 issues. However, there are several shortcomings
                 relative to the other three aspects. CSP appears to
                 have a rather limited deployment as yet and, more
                 crucially, existing policies exhibit a number of
                 weaknesses and misconfiguration errors. Moreover,
                 content security policies are not regularly updated to
                 ban insecure practices and remove unintended security
                 violations. We argue that many of these problems can be
                 fixed by better exploiting the monitoring facilities of
                 CSP, while other issues deserve additional research,
                 being more rooted into the CSP design.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "10",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Cacheda:2018:CPU,
  author =       "Fidel Cacheda and Roi Blanco and Nicola Barbieri",
  title =        "Characterizing and Predicting Users' Behavior on Local
                 Search Queries",
  journal =      j-TWEB,
  volume =       "12",
  number =       "2",
  pages =        "11:1--11:??",
  month =        jun,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3157059",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jun 28 14:10:01 MDT 2018",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The use of queries to find products and services that
                 are located nearby is increasing rapidly due mainly to
                 the ubiquity of internet access and location services
                 provided by smartphone devices. Local search engines
                 help users by matching queries with a predefined
                 geographical connotation (``local queries'') against a
                 database of local business listings. Local search
                 differs from traditional Web search because, to
                 correctly capture users' click behavior, the estimation
                 of relevance between query and candidate results must
                 be integrated with geographical signals, such as
                 distance. The intuition is that users prefer businesses
                 that are physically closer to them or in a convenient
                 area (e.g., close to their home). However, this notion
                 of closeness depends upon other factors, like the
                 business category, the quality of the service provided,
                 the density of businesses in the area of interest, the
                 hour of the day, or even the day of the week. In this
                 work, we perform an extensive analysis of online users'
                 interactions with a local search engine, investigating
                 their intent, temporal patterns, and highlighting
                 relationships between distance-to-business and other
                 factors, such as business reputation, Furthermore, we
                 investigate the problem of estimating the click-through
                 rate on local search ( LCTR ) by exploiting the
                 combination of standard retrieval methods with a rich
                 collection of geo-, user-, and business-dependent
                 features. We validate our approach on a large log
                 collected from a real-world local search service. Our
                 evaluation shows that the non-linear combination of
                 business and user information, geo-local and textual
                 relevance features leads to a significant improvements
                 over existing alternative approaches based on a
                 combination of relevance, distance, and business
                 reputation [1].",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "11",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Boldi:2018:BMC,
  author =       "Paolo Boldi and Andrea Marino and Massimo Santini and
                 Sebastiano Vigna",
  title =        "{BUbiNG}: Massive Crawling for the Masses",
  journal =      j-TWEB,
  volume =       "12",
  number =       "2",
  pages =        "12:1--12:26",
  month =        jun,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3160017",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jun 28 14:10:01 MDT 2018",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/java2010.bib;
                 http://www.math.utah.edu/pub/tex/bib/pagerank.bib;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/citation.cfm?doid=3176641.3160017",
  abstract =     "Although web crawlers have been around for twenty
                 years by now, there is virtually no freely available,
                 open-source crawling software that guarantees high
                 throughput, overcomes the limits of single-machine
                 systems, and, at the same time, scales linearly with
                 the amount of resources available. This article aims at
                 filling this gap, through the description of BUbiNG,
                 our next-generation web crawler built upon the authors'
                 experience with UbiCrawler [9] and on the last ten
                 years of research on the topic. BUbiNG is an
                 open-source Java fully distributed crawler; a single
                 BUbiNG agent, using sizeable hardware, can crawl
                 several thousand pages per second respecting strict
                 politeness constraints, both host- and IP-based. Unlike
                 existing open-source distributed crawlers that rely on
                 batch techniques (like MapReduce), BUbiNG job
                 distribution is based on modern high-speed protocols to
                 achieve very high throughput.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "12",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
  keywords =     "BUbiNG; centrality measures; distributed systems;
                 Java; PageRank; UbiCrawler; Web crawling",
}

@Article{Gaeta:2018:MID,
  author =       "Rossano Gaeta",
  title =        "A Model of Information Diffusion in Interconnected
                 Online Social Networks",
  journal =      j-TWEB,
  volume =       "12",
  number =       "2",
  pages =        "13:1--13:??",
  month =        jun,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3160000",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jun 28 14:10:01 MDT 2018",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Online social networks (OSN) have today reached a
                 remarkable capillary diffusion. There are numerous
                 examples of very large platforms people use to
                 communicate and maintain relationships. People also
                 subscribe to several OSNs, e.g., people create accounts
                 on Facebook, Twitter, and so on. This phenomenon leads
                 to online social internetworking (OSI) scenarios where
                 users who subscribe to multiple OSNs are termed as
                 bridges. Unfortunately, several important features make
                 the study of information propagation in an OSI scenario
                 a difficult task, e.g., correlations in both the
                 structural characteristics of OSNs and the bridge
                 interconnections among them, heterogeneity and size of
                 OSNs, activity factors, cross-posting propensity, and
                 so on. In this article, we propose a directed random
                 graph-based model that is amenable to efficient
                 numerical solution to analyze the phenomenon of
                 information propagation in an OSI scenario; in the
                 model development, we take into account heterogeneity
                 and correlations introduced by both topological
                 (correlations among nodes degrees and among bridge
                 distributions) and user-related factors (activity
                 index, cross-posting propensity). We first validate the
                 model predictions against simulations on snapshots of
                 interconnected OSNs in a reference scenario.
                 Subsequently, we exploit the model to show the impact
                 on the information propagation of several
                 characteristics of the reference scenario, i.e., size
                 and complexity of the OSI scenario, degree distribution
                 and overall number of bridges, growth and decline of
                 OSNs in time, and time-varying cross-posting users
                 propensity.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "13",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Davison:2018:TR,
  author =       "Brian D. Davison",
  title =        "2017 {TWEB} Reviewers",
  journal =      j-TWEB,
  volume =       "12",
  number =       "2",
  pages =        "14:1--14:??",
  month =        jun,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3209033",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jun 28 14:10:01 MDT 2018",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "14",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Fogli:2018:EQU,
  author =       "Daniela Fogli and Giovanni Guida",
  title =        "Evaluating Quality in Use of Corporate {Web} Sites: an
                 Empirical Investigation",
  journal =      j-TWEB,
  volume =       "12",
  number =       "3",
  pages =        "15:1--15:??",
  month =        jul,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3184646",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:06 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "In our prior work, we presented a novel approach to
                 the evaluation of quality in use of corporate web sites
                 based on an original quality model (QM-U) and a related
                 methodology (EQ-EVAL). This article focuses on two
                 research questions. The first one aims at investigating
                 whether expected quality obtained through the
                 application of EQ-EVAL methodology by employing a small
                 panel of evaluators is a good approximation of actual
                 quality obtained through experimentation with real
                 users. To answer this research question, a comparative
                 study has been carried out involving 5 evaluators and
                 50 real users. The second research question aims at
                 demonstrating that the adoption of the EQ-EVAL
                 methodology can provide useful information for web site
                 improvement. Three original indicators, namely
                 coherence, coverage and ranking have been defined to
                 answer this question, and an additional study comparing
                 the assessments of two panels of 5 and 10 evaluators,
                 respectively, has been carried out. The results
                 obtained in both studies are largely positive and
                 provide a rational support for the adoption of the
                 EQ-EVAL methodology.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "15",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Park:2018:LLB,
  author =       "Sangkeun Park and Mark S. Ackerman and Uichin Lee",
  title =        "Localness of Location-based Knowledge Sharing: a Study
                 of {Naver KiN} {``Here''}",
  journal =      j-TWEB,
  volume =       "12",
  number =       "3",
  pages =        "16:1--16:??",
  month =        jul,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/2983645",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:06 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "In location-based social Q8A services, people ask a
                 question with a high expectation that local residents
                 who have local knowledge will answer the question.
                 However, little is known about the locality of user
                 activities in location-based social Q8A services. This
                 study aims to deepen our understanding of
                 location-based knowledge sharing by investigating the
                 following: general behavioral characteristics of users,
                 the topical and typological patterns related to
                 geographic characteristics, geographic locality of user
                 activities, and motivations of local knowledge sharing.
                 To this end, we analyzed a 12-month period Q8A dataset
                 from Naver KiN ``Here,'' a location-based social Q8A
                 mobile app, in addition to a supplementary survey
                 dataset obtained from 285 mobile users. Our results
                 reveal several unique characteristics of location-based
                 social Q8A. When compared with conventional social Q8A
                 sites, users ask and answer different
                 topical/typological questions. In addition, those who
                 answer have a strong spatial locality wherein they
                 primarily have local knowledge in a few regions, in
                 areas such as their home and work. We also find unique
                 motivators such as ownership of local knowledge and a
                 sense of local community. The findings reported in the
                 article have significant implications for the design of
                 Q8A systems, especially location-based social Q8A
                 systems.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "16",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Rudra:2018:ESS,
  author =       "Koustav Rudra and Niloy Ganguly and Pawan Goyal and
                 Saptarshi Ghosh",
  title =        "Extracting and Summarizing Situational Information
                 from the {Twitter} Social Media during Disasters",
  journal =      j-TWEB,
  volume =       "12",
  number =       "3",
  pages =        "17:1--17:??",
  month =        jul,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3178541",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:06 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Microblogging sites like Twitter have become important
                 sources of real-time information during disaster
                 events. A large amount of valuable situational
                 information is posted in these sites during disasters;
                 however, the information is dispersed among hundreds of
                 thousands of tweets containing sentiments and opinions
                 of the masses. To effectively utilize microblogging
                 sites during disaster events, it is necessary to not
                 only extract the situational information from the large
                 amounts of sentiments and opinions, but also to
                 summarize the large amounts of situational information
                 posted in real-time. During disasters in countries like
                 India, a sizable number of tweets are posted in local
                 resource-poor languages besides the normal
                 English-language tweets. For instance, in the Indian
                 subcontinent, a large number of tweets are posted in
                 Hindi/Devanagari (the national language of India), and
                 some of the information contained in such non-English
                 tweets is not available (or available at a later point
                 of time) through English tweets. In this work, we
                 develop a novel classification-summarization framework
                 which handles tweets in both English and Hindi-we first
                 extract tweets containing situational information, and
                 then summarize this information. Our proposed
                 methodology is developed based on the understanding of
                 how several concepts evolve in Twitter during disaster.
                 This understanding helps us achieve superior
                 performance compared to the state-of-the-art tweet
                 classifiers and summarization approaches on English
                 tweets. Additionally, to our knowledge, this is the
                 first attempt to extract situational information from
                 non-English tweets.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "17",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Darari:2018:CMR,
  author =       "Fariz Darari and Werner Nutt and Giuseppe Pirr{\`o}
                 and Simon Razniewski",
  title =        "Completeness Management for {RDF} Data Sources",
  journal =      j-TWEB,
  volume =       "12",
  number =       "3",
  pages =        "18:1--18:??",
  month =        jul,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3196248",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:06 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The Semantic Web is commonly interpreted under the
                 open-world assumption, meaning that information
                 available (e.g., in a data source) captures only a
                 subset of the reality. Therefore, there is no certainty
                 about whether the available information provides a
                 complete representation of the reality. The broad aim
                 of this article is to contribute a formal study of how
                 to describe the completeness of parts of the Semantic
                 Web stored in RDF data sources. We introduce a
                 theoretical framework allowing augmentation of RDF data
                 sources with statements, also expressed in RDF, about
                 their completeness. One immediate benefit of this
                 framework is that now query answers can be complemented
                 with information about their completeness. We study the
                 impact of completeness statements on the complexity of
                 query answering by considering different fragments of
                 the SPARQL language, including the RDFS entailment
                 regime, and the federated scenario. We implement an
                 efficient method for reasoning about query completeness
                 and provide an experimental evaluation in the presence
                 of large sets of completeness statements.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "18",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Wang:2018:OWP,
  author =       "Yue Wang and Dawei Yin and Luo Jie and Pengyuan Wang
                 and Makoto Yamada and Yi Chang and Qiaozhu Mei",
  title =        "Optimizing Whole-Page Presentation for {Web} Search",
  journal =      j-TWEB,
  volume =       "12",
  number =       "3",
  pages =        "19:1--19:??",
  month =        jul,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3204461",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:06 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Modern search engines aggregate results from different
                 verticals: webpages, news, images, video, shopping,
                 knowledge cards, local maps, and so on. Unlike ``ten
                 blue links,'' these search results are heterogeneous in
                 nature and not even arranged in a list on the page.
                 This revolution directly challenges the conventional
                 ``ranked list'' formulation in ad hoc search.
                 Therefore, finding proper presentation for a gallery of
                 heterogeneous results is critical for modern search
                 engines. We propose a novel framework that learns the
                 optimal page presentation to render heterogeneous
                 results onto search result page (SERP). Page
                 presentation is broadly defined as the strategy to
                 present a set of items on SERP, much more expressive
                 than a ranked list. It can specify item positions,
                 image sizes, text fonts, and any other styles as long
                 as variations are within business and design
                 constraints. The learned presentation is content aware,
                 i.e., tailored to specific queries and returned
                 results. Simulation experiments show that the framework
                 automatically learns eye-catchy presentations for
                 relevant results. Experiments on real data show that
                 simple instantiations of the framework already
                 outperform leading algorithm in federated search result
                 presentation. It means the framework can learn its own
                 result presentation strategy purely from data, without
                 even knowing the ``probability ranking principle.''",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "19",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Mula:2018:FBE,
  author =       "Wojciech Mu{\l}a and Daniel Lemire",
  title =        "Faster {Base64} Encoding and Decoding Using {AVX2}
                 Instructions",
  journal =      j-TWEB,
  volume =       "12",
  number =       "3",
  pages =        "20:1--20:??",
  month =        jul,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3132709",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:06 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/java2010.bib;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Web developers use base64 formats to include images,
                 fonts, sounds, and other resources directly inside
                 HTML, JavaScript, JSON, and XML files. We estimate that
                 billions of base64 messages are decoded every day. We
                 are motivated to improve the efficiency of base64
                 encoding and decoding. Compared to state-of-the-art
                 implementations, we multiply the speeds of both the
                 encoding ( \approx 10 $ \times $0) and the decoding (
                 \approx 7 $ \times $). We achieve these good results by
                 using the single-instruction-multiple-data instructions
                 available on recent Intel processors (AVX2). Our
                 accelerated software abides by the specification and
                 reports errors when encountering characters outside of
                 the base64 set. It is available online as free software
                 under a liberal license.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "20",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Parisi:2018:TKU,
  author =       "Francesco Parisi and Noseong Park and Andrea Pugliese
                 and V. S. Subrahmanian",
  title =        "Top-k User-Defined Vertex Scoring Queries in
                 Edge-Labeled Graph Databases",
  journal =      j-TWEB,
  volume =       "12",
  number =       "4",
  pages =        "21:1--21:??",
  month =        nov,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3213891",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:06 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "We consider identifying highly ranked vertices in
                 large graph databases such as social networks or the
                 Semantic Web where there are edge labels. There are
                 many applications where users express scoring queries
                 against such databases that involve two elements: (i) a
                 set of patterns describing relationships that a vertex
                 of interest to the user must satisfy and (ii) a scoring
                 mechanism in which the user may use properties of the
                 vertex to assign a score to that vertex. We define the
                 concept of a partial pattern map query (partial
                 PM-query), which intuitively allows us to prune partial
                 matchings, and show that finding an optimal partial
                 PM-query is NP-hard. We then propose two algorithms,
                 PScore_LP and PScore_NWST, to find the answer to a
                 scoring (top- k ) query. In PScore_LP, the optimal
                 partial PM-query is found using a list-oriented pruning
                 method. PScore_NWST leverages node-weighted Steiner
                 trees to quickly compute slightly sub-optimal
                 solutions. We conduct detailed experiments comparing
                 our algorithms with (i) an algorithm (PScore_Base) that
                 computes all answers to the query, evaluates them
                 according to the scoring method, and chooses the top-
                 k, and (ii) two Semantic Web query processing systems
                 (Jena and GraphDB). Our algorithms show better
                 performance than PScore_Base and the Semantic Web query
                 processing systems-moreover, PScore_NWST outperforms
                 PScore_LP on large queries and on queries with a tree
                 structure.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "21",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Fanou:2018:EAA,
  author =       "Rod{\'e}rick Fanou and Gareth Tyson and Eder Leao
                 Fernandes and Pierre Francois and Francisco Valera and
                 Arjuna Sathiaseelan",
  title =        "Exploring and Analysing the {African} {Web}
                 Ecosystem",
  journal =      j-TWEB,
  volume =       "12",
  number =       "4",
  pages =        "22:1--22:??",
  month =        nov,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3213897",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:06 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "It is well known that internet infrastructure
                 deployment is progressing at a rapid pace in the
                 African continent. A flurry of recent research has
                 quantified this, highlighting the expansion of its
                 underlying connectivity network. However, improving the
                 infrastructure is not useful without appropriately
                 provisioned services to exploit it. This article
                 measures the availability and utilisation of web
                 infrastructure in Africa. Whereas others have explored
                 web infrastructure in developed regions, we shed light
                 on practices in developing regions. To achieve this, we
                 apply a comprehensive measurement methodology to
                 collect data from a variety of sources. We first focus
                 on Google to reveal that its content infrastructure in
                 Africa is, indeed, expanding. That said, we find that
                 much of its web content is still served from the US and
                 Europe, despite being the most popular website in many
                 African countries. We repeat the same analysis across a
                 number of other regionally popular websites to find
                 that even top African websites prefer to host their
                 content abroad. To explore the reasons for this, we
                 evaluate some of the major bottlenecks facing content
                 delivery networks (CDNs) in Africa. Amongst other
                 factors, we find a lack of peering between the networks
                 hosting our probes, preventing the sharing of CDN
                 servers, as well as poorly configured DNS resolvers.
                 Finally, our mapping of middleboxes in the region
                 reveals that there is a greater presence of transparent
                 proxies in Africa than in Europe or the US. We conclude
                 the work with a number of suggestions for alleviating
                 the issues observed.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "22",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Torre-Bastida:2018:RBT,
  author =       "Ana I. Torre-Bastida and Jes{\'u}s Berm{\'u}dez and
                 Arantza Illarramendi",
  title =        "A Rule-Based Transducer for Querying Incompletely
                 Aligned Datasets",
  journal =      j-TWEB,
  volume =       "12",
  number =       "4",
  pages =        "23:1--23:??",
  month =        nov,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3228328",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:06 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "A growing number of Linked Open Data sources (from
                 diverse provenances and about different domains) that
                 can be freely browsed and searched to find and extract
                 useful information have been made available. However,
                 access to them is difficult for different reasons. This
                 study addresses access issues concerning heterogeneity.
                 It is common for datasets to describe the same or
                 overlapping domains while using different vocabularies.
                 Our study presents a transducer that transforms a
                 SPARQL query suitably expressed in terms of the
                 vocabularies used in a source dataset into another
                 SPARQL query suitably expressed for a target dataset
                 involving different vocabularies. The transformation is
                 based on existing alignments between terms in different
                 datasets. Whenever the transducer is unable to produce
                 a semantically equivalent query because of the scarcity
                 of term alignments, the transducer produces a semantic
                 approximation of the query to avoid returning the empty
                 answer to the user. Transformation across datasets is
                 achieved through the management of a wide range of
                 transformation rules. The feasibility of our proposal
                 has been validated with a prototype implementation that
                 processes queries that appear in well-known benchmarks
                 and SPARQL endpoint logs. Results of the experiments
                 show that the system is quite effective in achieving
                 adequate transformations.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "23",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Vassio:2018:YWY,
  author =       "Luca Vassio and Idilio Drago and Marco Mellia and Zied
                 {Ben Houidi} and Mohamed Lamine Lamali",
  title =        "You, the {Web}, and Your Device: Longitudinal
                 Characterization of Browsing Habits",
  journal =      j-TWEB,
  volume =       "12",
  number =       "4",
  pages =        "24:1--24:??",
  month =        nov,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3231466",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:06 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Understanding how people interact with the web is key
                 for a variety of applications, e.g., from the design of
                 effective web pages to the definition of successful
                 online marketing campaigns. Browsing behavior has been
                 traditionally represented and studied by means of
                 clickstreams, i.e., graphs whose vertices are web
                 pages, and edges are the paths followed by users.
                 Obtaining large and representative data to extract
                 clickstreams is, however, challenging. The evolution of
                 the web questions whether browsing behavior is changing
                 and, by consequence, whether properties of clickstreams
                 are changing. This article presents a longitudinal
                 study of clickstreams from 2013 to 2016. We evaluate an
                 anonymized dataset of HTTP traces captured in a large
                 ISP, where thousands of households are connected. We
                 first propose a methodology to identify actual URLs
                 requested by users from the massive set of requests
                 automatically fired by browsers when rendering web
                 pages. Then, we characterize web usage patterns and
                 clickstreams, taking into account both the temporal
                 evolution and the impact of the device used to explore
                 the web. Our analyses precisely quantify various
                 aspects of clickstreams and uncover interesting
                 patterns, such as the typical short paths followed by
                 people while navigating the web, the fast increasing
                 trend in browsing from mobile devices, and the
                 different roles of search engines and social networks
                 in promoting content. Finally, we contribute a dataset
                 of anonymized clickstreams to the community to foster
                 new studies.\&lt;sup;\&gt;1\&lt;/sup;\&gt;",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "24",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Gong:2018:UCS,
  author =       "Qingyuan Gong and Yang Chen and Jiyao Hu and Qiang Cao
                 and Pan Hui and Xin Wang",
  title =        "Understanding Cross-Site Linking in Online Social
                 Networks",
  journal =      j-TWEB,
  volume =       "12",
  number =       "4",
  pages =        "25:1--25:??",
  month =        nov,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3213898",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:06 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "As a result of the blooming of online social networks
                 (OSNs), a user often holds accounts on multiple sites.
                 In this article, we study the emerging ``cross-site
                 linking'' function available on mainstream OSN services
                 including Foursquare, Quora, and Pinterest. We first
                 conduct a data-driven analysis on crawled profiles and
                 social connections of all 61.39 million Foursquare
                 users to obtain a thorough understanding of this
                 function. Our analysis has shown that the cross-site
                 linking function is adopted by 57.10\% of all
                 Foursquare users, and the users who have enabled this
                 function are more active than others. We also find that
                 the enablement of cross-site linking might lead to
                 privacy risks. Based on cross-site links between
                 Foursquare and external OSN sites, we formulate
                 cross-site information aggregation as a problem that
                 uses cross-site links to stitch together site-local
                 information fields for OSN users. Using large datasets
                 collected from Foursquare, Facebook, and Twitter, we
                 demonstrate the usefulness and the challenges of
                 cross-site information aggregation. In addition to the
                 measurements, we carry out a survey collecting detailed
                 user feedback on cross-site linking. This survey
                 studies why people choose to or not to enable
                 cross-site linking, as well as the motivation and
                 concerns of enabling this function.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "25",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Cui:2018:UDR,
  author =       "Yi Cui and Clint Sparkman and Hsin-Tsang Lee and
                 Dmitri Loguinov",
  title =        "Unsupervised Domain Ranking in Large-Scale {Web}
                 Crawls",
  journal =      j-TWEB,
  volume =       "12",
  number =       "4",
  pages =        "26:1--26:??",
  month =        nov,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3182180",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:06 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/pagerank.bib;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "With the proliferation of web spam and infinite
                 autogenerated web content, large-scale web crawlers
                 require low-complexity ranking methods to effectively
                 budget their limited resources and allocate bandwidth
                 to reputable sites. In this work, we assume crawls that
                 produce frontiers orders of magnitude larger than RAM,
                 where sorting of pending URLs is infeasible in real
                 time. Under these constraints, the main objective is to
                 quickly compute domain budgets and decide which of them
                 can be massively crawled. Those ranked at the top of
                 the list receive aggressive crawling allowances, while
                 all other domains are visited at some small default
                 rate. To shed light on Internet-wide spam avoidance, we
                 study topology-based ranking algorithms on domain-level
                 graphs from the two largest academic crawls: a
                 6.3B-page IRLbot dataset and a 1B-page ClueWeb09
                 exploration. We first propose a new methodology for
                 comparing the various rankings and then show that
                 in-degree BFS-based techniques decisively outperform
                 classic PageRank-style methods, including TrustRank.
                 However, since BFS requires several orders of magnitude
                 higher overhead and is generally infeasible for
                 real-time use, we propose a fast, accurate, and
                 scalable estimation method called TSE that can achieve
                 much better crawl prioritization in practice. It is
                 especially beneficial in applications with limited
                 hardware resources.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "26",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{An:2018:IPR,
  author =       "J. An and H. Kwak and S. Jung and J. Salminen and M.
                 Admad and B. Jansen",
  title =        "Imaginary People Representing Real Numbers: Generating
                 Personas from Online Social Media Data",
  journal =      j-TWEB,
  volume =       "12",
  number =       "4",
  pages =        "27:1--27:??",
  month =        nov,
  year =         "2018",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3265986",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:06 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "We develop a methodology to automate creating
                 imaginary people, referred to as personas, by
                 processing complex behavioral and demographic data of
                 social media audiences. From a popular social media
                 account containing more than 30 million interactions by
                 viewers from 198 countries engaging with more than
                 4,200 online videos produced by a global media
                 corporation, we demonstrate that our methodology has
                 several novel accomplishments, including: (a)
                 identifying distinct user behavioral segments based on
                 the user content consumption patterns; (b) identifying
                 impactful demographics groupings; and (c) creating rich
                 persona descriptions by automatically adding pertinent
                 attributes, such as names, photos, and personal
                 characteristics. We validate our approach by
                 implementing the methodology into an actual working
                 system; we then evaluate it via quantitative methods by
                 examining the accuracy of predicting content preference
                 of personas, the stability of the personas over time,
                 and the generalizability of the method via applying to
                 two other datasets. Research findings show the approach
                 can develop rich personas representing the behavior and
                 demographics of real audiences using privacy-preserving
                 aggregated online social media data from major online
                 platforms. Results have implications for media
                 companies and other organizations distributing content
                 via online platforms.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "27",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Wilson:2019:APP,
  author =       "Shomir Wilson and Florian Schaub and Frederick Liu and
                 Kanthashree Mysore Sathyendra and Daniel Smullen and
                 Sebastian Zimmeck and Rohan Ramanath and Peter Story
                 and Fei Liu and Norman Sadeh and Noah A. Smith",
  title =        "Analyzing Privacy Policies at Scale: From
                 Crowdsourcing to Automated Annotations",
  journal =      j-TWEB,
  volume =       "13",
  number =       "1",
  pages =        "1:1--1:??",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3230665",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:06 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Website privacy policies are often long and difficult
                 to understand. While research shows that Internet users
                 care about their privacy, they do not have the time to
                 understand the policies of every website they visit,
                 and most users hardly ever read privacy policies. Some
                 recent efforts have aimed to use a combination of
                 crowdsourcing, machine learning, and natural language
                 processing to interpret privacy policies at scale, thus
                 producing annotations for use in interfaces that inform
                 Internet users of salient policy details. However,
                 little attention has been devoted to studying the
                 accuracy of crowdsourced privacy policy annotations,
                 how crowdworker productivity can be enhanced for such a
                 task, and the levels of granularity that are feasible
                 for automatic analysis of privacy policies. In this
                 article, we present a trajectory of work addressing
                 each of these topics. We include analyses of
                 crowdworker performance, evaluation of a method to make
                 a privacy-policy oriented task easier for crowdworkers,
                 a coarse-grained approach to labeling segments of
                 policy text with descriptive themes, and a fine-grained
                 approach to identifying user choices described in
                 policy text. Together, the results from these efforts
                 show the effectiveness of using automated and
                 semi-automated methods for extracting from privacy
                 policies the data practice details that are salient to
                 Internet users' interests.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "1",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Athanasopoulos:2019:MAX,
  author =       "Dionysis Athanasopoulos and Apostolos Zarras",
  title =        "Mining Abstract {XML} Data-Types",
  journal =      j-TWEB,
  volume =       "13",
  number =       "1",
  pages =        "2:1--2:??",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3267467",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:06 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Schema integration has been a long-standing challenge
                 for the data-engineering community that has received
                 steady attention over the past three decades.
                 General-purpose integration approaches construct
                 unified schemas that encompass all schema elements.
                 Schema integration has been revisited in the past
                 decade in service-oriented computing since the
                 input/output data-types of service interfaces are
                 heterogeneous XML schemas. However, service integration
                 differs from the traditional integration problem, since
                 it should generalize schemas (mining abstract
                 data-types) instead of unifying all schema elements. To
                 mine well-formed abstract data-types, the fundamental
                 Liskov Substitution Principle (LSP), which generally
                 holds between abstract data-types and their subtypes,
                 should be followed. However, due to the heterogeneity
                 of service data-types, the strict employment of LSP is
                 not usually feasible. On top of that, XML offers a rich
                 type system, based on which data-types are defined via
                 combining type patterns (e.g., composition,
                 aggregation). The existing integration approaches have
                 not dealt with the challenges of a defining subtyping
                 relation between XML type patterns. To address these
                 challenges, we propose a relaxed version of LSP between
                 XML type patterns and an automated generalization
                 process for mining abstract XML data-types. We evaluate
                 the effectiveness and the efficiency of the process on
                 the schemas of two datasets against two representative
                 state-of-the-art approaches.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "2",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Anisetti:2019:TBS,
  author =       "Marco Anisetti and Claudio Ardagna and Ernesto Damiani
                 and Gianluca Polegri",
  title =        "Test-Based Security Certification of Composite
                 Services",
  journal =      j-TWEB,
  volume =       "13",
  number =       "1",
  pages =        "3:1--3:??",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3267468",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:06 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "The diffusion of service-based and cloud-based systems
                 has created a scenario where software is often made
                 available as services, offered as commodities over
                 corporate networks or the global net. This scenario
                 supports the definition of business processes as
                 composite services, which are implemented via either
                 static or runtime composition of offerings provided by
                 different suppliers. Fast and accurate evaluation of
                 services' security properties becomes then a
                 fundamental requirement and is nowadays part of the
                 software development process. In this article, we show
                 how the verification of security properties of
                 composite services can be handled by test-based
                 security certification and built to be effective and
                 efficient in dynamic composition scenarios. Our
                 approach builds on existing security certification
                 schemes for monolithic services and extends them
                 towards service compositions. It virtually certifies
                 composite services, starting from certificates awarded
                 to the component services. We describe three heuristic
                 algorithms for generating runtime test-based evidence
                 of the composite service holding the properties. These
                 algorithms are compared with the corresponding
                 exhaustive algorithm to evaluate their quality and
                 performance. We also evaluate the proposed approach in
                 a real-world industrial scenario, which considers
                 ENGpay online payment system of Engineering Ingegneria
                 Informatica S.p.A. The proposed industrial evaluation
                 presents the utility and generality of the proposed
                 approach by showing how certification results can be
                 used as a basis to establish compliance to Payment Card
                 Industry Data Security Standard.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "3",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Redmiles:2019:NPW,
  author =       "Elissa M. Redmiles and Eszter Hargittai",
  title =        "New Phone, Who Dis? {Modeling} Millennials' Backup
                 Behavior",
  journal =      j-TWEB,
  volume =       "13",
  number =       "1",
  pages =        "4:1--4:??",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3208105",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:06 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Given the ever-rising frequency of malware attacks and
                 other problems leading people to lose their files,
                 backups are an important proactive protective behavior
                 in which users can engage. Backing up files can prevent
                 emotional and financial losses and improve overall user
                 experience. Yet, we find that less than half of young
                 adults perform mobile or computer backups regularly. To
                 understand why, we model the factors that drive mobile
                 and computer backup behavior, and changes in that
                 behavior over time, using data from a panel survey of
                 384 diverse young adults. We develop a set of models
                 that explain 37\% and 38\% of the variance in reported
                 mobile and computer backup behaviors, respectively.
                 These models show consistent relationships between
                 Internet skills and backup frequency on both mobile and
                 computer devices. We find that this relationship holds
                 longitudinally: increases in Internet skills lead to
                 increased frequency of computer backups. This article
                 provides a foundation for understanding what drives
                 young adults' backup behavior. It concludes with
                 recommendations for motivating people to back up, and
                 for future work, modeling similar user behaviors.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "4",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Calegari:2019:WPH,
  author =       "Patrice Calegari and Marc Levrier and Pawe{\l}
                 Balczy{\'n}ski",
  title =        "{Web} Portals for High-performance Computing: a
                 Survey",
  journal =      j-TWEB,
  volume =       "13",
  number =       "1",
  pages =        "5:1--5:??",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3197385",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:06 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/java2010.bib;
                 http://www.math.utah.edu/pub/tex/bib/super.bib;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "This article addresses web interfaces for
                 High-performance Computing (HPC) simulation software.
                 First, it presents a brief history, starting in the
                 1990s with Java applets, of web interfaces used for
                 accessing and making best possible use of remote HPC
                 resources. It introduces HPC web-based portal use
                 cases. Then it identifies and discusses the key
                 features, among functional and non-functional
                 requirements, that characterize such portals. A brief
                 state of the art is then presented. The design and
                 development of Bull extreme factory Computing Studio v3
                 (XCS3) is chosen as a common thread for showing how the
                 identified key features can all be implemented in one
                 software: multi-tenancy, multi-scheduler compatibility,
                 complete control through an HTTP RESTful API,
                 customizable user interface with Responsive Web Design,
                 HPC application template framework, remote
                 visualization, and access through the Authentication,
                 Authorization, and Accounting security framework with
                 the Role-Based Access Control permission model.
                 Non-functional requirements (security, usability,
                 performance, reliability) are discussed, and the
                 article concludes by giving perspective for future
                 work.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "5",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Romero:2019:SNU,
  author =       "Daniel M. Romero and Brian Uzzi and Jon Kleinberg",
  title =        "Social Networks under Stress: Specialized Team Roles
                 and Their Communication Structure",
  journal =      j-TWEB,
  volume =       "13",
  number =       "1",
  pages =        "6:1--6:??",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3295460",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:06 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Social network research has begun to take advantage of
                 fine-grained communications regarding coordination,
                 decision-making, and knowledge sharing. These studies,
                 however, have not generally analyzed how external
                 events are associated with a social network's structure
                 and communicative properties. Here, we study how
                 external events are associated with a network's change
                 in structure and communications. Analyzing a complete
                 dataset of millions of instant messages among the
                 decision-makers with different roles in a large hedge
                 fund and their network of outside contacts, we
                 investigate the link between price shocks, network
                 structure, and change in the affect and cognition of
                 decision-makers embedded in the network. We also
                 analyze the communication dynamics among specialized
                 teams in the organization. When price shocks occur the
                 communication network tends not to display structural
                 changes associated with adaptiveness such as the
                 activation of weak ties to obtain novel information.
                 Rather, the network ``turtles up.'' It displays a
                 propensity for higher clustering, strong tie
                 interaction, and an intensification of insider vs.
                 outsider and within-role vs. between-role
                 communication. Further, we find changes in network
                 structure predict shifts in cognitive and affective
                 processes, execution of new transactions, and local
                 optimality of transactions better than prices,
                 revealing the important predictive relationship between
                 network structure and collective behavior within a
                 social network.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "6",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Gilani:2019:LSB,
  author =       "Zafar Gilani and Reza Farahbakhsh and Gareth Tyson and
                 Jon Crowcroft",
  title =        "A Large-scale Behavioural Analysis of Bots and Humans
                 on {Twitter}",
  journal =      j-TWEB,
  volume =       "13",
  number =       "1",
  pages =        "7:1--7:??",
  month =        feb,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3298789",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:06 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Recent research has shown a substantial active
                 presence of bots in online social networks (OSNs). In
                 this article, we perform a comparative analysis of the
                 usage and impact of bots and humans on Twitter-one of
                 the largest OSNs in the world. We collect a large-scale
                 Twitter dataset and define various metrics based on
                 tweet metadata. Using a human annotation task, we
                 assign ``bot'' and ``human'' ground-truth labels to the
                 dataset and compare the annotations against an online
                 bot detection tool for evaluation. We then ask a series
                 of questions to discern important behavioural
                 characteristics of bots and humans using metrics within
                 and among four popularity groups. From the comparative
                 analysis, we draw clear differences and interesting
                 similarities between the two entities.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "7",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Thoma:2019:FEC,
  author =       "Steffen Thoma and Andreas Thalhammer and Andreas Harth
                 and Rudi Studer",
  title =        "{FusE}: Entity-Centric Data Fusion on Linked Data",
  journal =      j-TWEB,
  volume =       "13",
  number =       "2",
  pages =        "8:1--8:??",
  month =        apr,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3306128",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:07 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3306128",
  abstract =     "Many current web pages include structured data which
                 can directly be processed and used. Search engines, in
                 particular, gather that structured data and provide
                 question answering capabilities over the integrated
                 data with an entity-centric presentation of the
                 results. Due to the decentralized nature of the web,
                 multiple structured data sources can provide similar
                 information about an entity. But data from different
                 sources may involve different vocabularies and modeling
                 granularities, which makes integration difficult. We
                 present FusE, an approach that identifies similar
                 entity-specific data across sources, independent of the
                 vocabulary and data modeling choices. We apply our
                 method along the scenario of a trustable knowledge
                 panel, conduct experiments in which we identify and
                 process entity data from web sources, and compare the
                 output to a competing system. The results underline the
                 advantages of the presented entity-centric data fusion
                 approach.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "8",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Alarte:2019:WWT,
  author =       "Juli{\'a}n Alarte and Josep Silva and Salvador
                 Tamarit",
  title =        "What {Web} Template Extractor Should {I} Use? {A}
                 Benchmarking and Comparison for Five Template
                 Extractors",
  journal =      j-TWEB,
  volume =       "13",
  number =       "2",
  pages =        "9:1--9:??",
  month =        apr,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3316810",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:07 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3316810",
  abstract =     "A Web template is a resource that implements the
                 structure and format of a website, making it ready for
                 plugging content into already formatted and prepared
                 pages. For this reason, templates are one of the main
                 development resources for website engineers, because
                 they increase productivity. Templates are also useful
                 for the final user, because they provide uniformity and
                 a common look and feel for all webpages. However, from
                 the point of view of crawlers and indexers, templates
                 are an important problem, because templates usually
                 contain irrelevant information, such as advertisements,
                 menus, and banners. Processing and storing this
                 information leads to a waste of resources (storage
                 space, bandwidth, etc.). It has been measured that
                 templates represent between 40\% and 50\% of data on
                 the Web. Therefore, identifying templates is essential
                 for indexing tasks. There exist many techniques and
                 tools for template extraction, but, unfortunately, it
                 is not clear at all which template extractor should a
                 user/system use, because they have never been compared,
                 and because they present different (complementary)
                 features such as precision, recall, and efficiency. In
                 this work, we compare the most advanced template
                 extractors. We implemented and evaluated five of the
                 most advanced template extractors in the literature. To
                 compare all of them, we implemented a workbench, where
                 they have been integrated and evaluated. Thanks to this
                 workbench, we can provide a fair empirical comparison
                 of all methods using the same benchmarks, technology,
                 implementation language, and evaluation criteria.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "9",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Vicario:2019:PFN,
  author =       "Michela {Del Vicario} and Walter Quattrociocchi and
                 Antonio Scala and Fabiana Zollo",
  title =        "Polarization and Fake News: Early Warning of Potential
                 Misinformation Targets",
  journal =      j-TWEB,
  volume =       "13",
  number =       "2",
  pages =        "10:1--10:??",
  month =        apr,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3316809",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:07 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3316809",
  abstract =     "Users' polarization and confirmation bias play a key
                 role in misinformation spreading on online social
                 media. Our aim is to use this information to determine
                 in advance potential targets for hoaxes and fake news.
                 In this article, we introduce a framework for promptly
                 identifying polarizing content on social media and,
                 thus, ``predicting'' future fake news topics. We
                 validate the performances of the proposed methodology
                 on a massive Italian Facebook dataset, showing that we
                 are able to identify topics that are susceptible to
                 misinformation with 77\% accuracy. Moreover, such
                 information may be embedded as a new feature in an
                 additional classifier able to recognize fake news with
                 91\% accuracy. The novelty of our approach consists in
                 taking into account a series of characteristics related
                 to users' behavior on online social media such as
                 Facebook, making a first, important step towards the
                 mitigation of misinformation phenomena by supporting
                 the identification of potential misinformation targets
                 and thus the design of tailored counter-narratives.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "10",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Cresci:2019:CPU,
  author =       "Stefano Cresci and Fabrizio Lillo and Daniele Regoli
                 and Serena Tardelli and Maurizio Tesconi",
  title =        "Cashtag Piggybacking: Uncovering Spam and Bot Activity
                 in Stock Microblogs on {Twitter}",
  journal =      j-TWEB,
  volume =       "13",
  number =       "2",
  pages =        "11:1--11:??",
  month =        apr,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3313184",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:07 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3313184",
  abstract =     "Microblogs are increasingly exploited for predicting
                 prices and traded volumes of stocks in financial
                 markets. However, it has been demonstrated that much of
                 the content shared in microblogging platforms is
                 created and publicized by bots and spammers. Yet, the
                 presence (or lack thereof) and the impact of fake stock
                 microblogs has never been systematically investigated
                 before. Here, we study 9M tweets related to stocks of
                 the five main financial markets in the US. By comparing
                 tweets with financial data from Google Finance, we
                 highlight important characteristics of Twitter stock
                 microblogs. More importantly, we uncover a malicious
                 practice-referred to as cashtag piggybacking
                 -perpetrated by coordinated groups of bots and likely
                 aimed at promoting low-value stocks by exploiting the
                 popularity of high-value ones. Among the findings of
                 our study is that as much as 71\% of the authors of
                 suspicious financial tweets are classified as bots by a
                 state-of-the-art spambot-detection algorithm.
                 Furthermore, 37\% of them were suspended by Twitter a
                 few months after our investigation. Our results call
                 for the adoption of spam- and bot-detection techniques
                 in all studies and applications that exploit
                 user-generated content for predicting the stock
                 market.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "11",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Watanabe:2019:LCP,
  author =       "Willian Massami Watanabe and Giovana L{\'a}zaro
                 Am{\^e}ndola and Fagner Christian Paes",
  title =        "Layout Cross-Platform and Cross-Browser
                 Incompatibilities Detection using Classification of
                 {DOM} Elements",
  journal =      j-TWEB,
  volume =       "13",
  number =       "2",
  pages =        "12:1--12:??",
  month =        apr,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3316808",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:07 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3316808",
  abstract =     "Web applications can be accessed through a variety of
                 user agent configurations, in which the browser,
                 platform, and device capabilities are not under the
                 control of developers. In order to grant the
                 compatibility of a web application in each environment,
                 developers must manually inspect their web application
                 in a wide variety of devices, platforms, and browsers.
                 Web applications can be rendered inconsistently
                 depending on the browser, the platform, and the device
                 capabilities which are used. Furthermore, the devices'
                 different viewport widths impact the way web
                 applications are rendered in them, in which elements
                 can be resized and change their absolute positions in
                 the display. These adaptation strategies must also be
                 considered in automatic incompatibility detection
                 approaches in the state of the art. Hence, we propose a
                 classification approach for detecting Layout
                 Cross-platform and Cross-browser incompatibilities,
                 which considers the adaptation strategies used in
                 responsive web applications. Our approach is an
                 extension of previous Cross-browser incompatibility
                 detection approaches and has the goal of reducing the
                 cost associated with manual inspections in different
                 devices, platforms, and browsers, by automatically
                 detecting Layout incompatibilities in this scenario.
                 The proposed approach classifies each DOM element which
                 composes a web application as an incompatibility or
                 not, based on its attributes, position, alignment,
                 screenshot, and the viewport width of the browser. We
                 report the results of an experiment conducted with 42
                 Responsive Web Applications, rendered in three devices
                 (Apple iPhone SE, Apple iPhone 8 Plus, and Motorola
                 Moto G4) and browsers (Google Chrome and Apple Safari).
                 The results (with F-measure of 0.70) showed evidence
                 which quantify the effectiveness of our classification
                 approach, and it could be further enhanced for
                 detecting Cross-platform and Cross-browser
                 incompatibilities. Furthermore, in the experiment, our
                 approach also performed better when compared to a
                 former state-of-the-art classification technique for
                 Cross-browser incompatibilities detection.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "12",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Sigg:2019:EUP,
  author =       "Stephan Sigg and Eemil Lagerspetz and Ella Peltonen
                 and Petteri Nurmi and Sasu Tarkoma",
  title =        "Exploiting Usage to Predict Instantaneous App
                 Popularity: Trend Filters and Retention Rates",
  journal =      j-TWEB,
  volume =       "13",
  number =       "2",
  pages =        "13:1--13:??",
  month =        apr,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3199677",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:07 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3199677",
  abstract =     "Popularity of mobile apps is traditionally measured by
                 metrics such as the number of downloads, installations,
                 or user ratings. A problem with these measures is that
                 they reflect usage only indirectly. Indeed, retention
                 rates, i.e., the number of days users continue to
                 interact with an installed app, have been suggested to
                 predict successful app lifecycles. We conduct the first
                 independent and large-scale study of retention rates
                 and usage trends on a dataset of app-usage data from a
                 community of 339,842 users and more than 213,667 apps.
                 Our analysis shows that, on average, applications lose
                 65\% of their users in the first week, while very
                 popular applications (top 100) lose only 35\%. It also
                 reveals, however, that many applications have more
                 complex usage behaviour patterns due to seasonality,
                 marketing, or other factors. To capture such effects,
                 we develop a novel app-usage trend measure which
                 provides instantaneous information about the popularity
                 of an application. Analysis of our data using this
                 trend filter shows that roughly 40\% of all apps never
                 gain more than a handful of users ( Marginal apps).
                 Less than 0.1\% of the remaining 60\% are constantly
                 popular ( Dominant apps), 1\% have a quick drain of
                 usage after an initial steep rise ( Expired apps), and
                 6\% continuously rise in popularity ( Hot apps). From
                 these, we can distinguish, for instance, trendsetters
                 from copycat apps. We conclude by demonstrating that
                 usage behaviour trend information can be used to
                 develop better mobile app recommendations.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "13",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Alorainy:2019:EAU,
  author =       "Wafa Alorainy and Pete Burnap and Han Liu and Matthew
                 L. Williams",
  title =        "{``The Enemy Among Us''}: Detecting Cyber Hate Speech
                 with Threats-based Othering Language Embeddings",
  journal =      j-TWEB,
  volume =       "13",
  number =       "3",
  pages =        "14:1--14:??",
  month =        oct,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3324997",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:07 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3324997",
  abstract =     "Offensive or antagonistic language targeted at
                 individuals and social groups based on their personal
                 characteristics (also known as cyber hate speech or
                 cyberhate) has been frequently posted and widely
                 circulated via the World Wide Web. This can be
                 considered as a key risk factor for individual and
                 societal tension surrounding regional instability.
                 Automated Web-based cyberhate detection is important
                 for observing and understanding community and regional
                 societal tension-especially in online social networks
                 where posts can be rapidly and widely viewed and
                 disseminated. While previous work has involved using
                 lexicons, bags-of-words, or probabilistic language
                 parsing approaches, they often suffer from a similar
                 issue, which is that cyberhate can be subtle and
                 indirect-thus, depending on the occurrence of
                 individual words or phrases, can lead to a significant
                 number of false negatives, providing inaccurate
                 representation of the trends in cyberhate. This problem
                 motivated us to challenge thinking around the
                 representation of subtle language use, such as
                 references to perceived threats from ``the other''
                 including immigration or job prosperity in a hateful
                 context. We propose a novel ``othering'' feature set
                 that utilizes language use around the concept of
                 ``othering'' and intergroup threat theory to identify
                 these subtleties, and we implement a wide range of
                 classification methods using embedding learning to
                 compute semantic distances between parts of speech
                 considered to be part of an ``othering'' narrative. To
                 validate our approach, we conducted two sets of
                 experiments. The first involved comparing the results
                 of our novel method with state-of-the-art baseline
                 models from the literature. Our approach outperformed
                 all existing methods. The second tested the best
                 performing models from the first phase on unseen
                 datasets for different types of cyberhate, namely
                 religion, disability, race, and sexual orientation. The
                 results showed F-measure scores for classifying hateful
                 instances obtained through applying our model of 0.81,
                 0.71, 0.89, and 0.72, respectively, demonstrating the
                 ability of the ``othering'' narrative to be an
                 important part of model generalization.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "14",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Zhao:2019:USE,
  author =       "Liping Zhao and Pericles Loucopoulos and Evangelia
                 Kavakli and Keletso J. Letsholo",
  title =        "User Studies on End-User Service Composition: a
                 Literature Review and a Design Framework",
  journal =      j-TWEB,
  volume =       "13",
  number =       "3",
  pages =        "15:1--15:??",
  month =        oct,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3340294",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:07 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3340294",
  abstract =     "Context: End-user service composition (EUSC) is a
                 service-oriented paradigm that aims to empower end
                 users and allow them to compose their own web
                 applications from reusable service components. User
                 studies have been used to evaluate EUSC tools and
                 processes. Such an approach should benefit software
                 development, because incorporating end users' feedback
                 into software development should make software more
                 useful and usable. Problem: There is a gap in our
                 understanding of what constitutes a user study and how
                 a good user study should be designed, conducted, and
                 reported. Goal: This article aims to address this gap.
                 Method: The article presents a systematic review of 47
                 selected user studies for EUSC. Guided by a review
                 framework, the article systematically and consistently
                 assesses the focus, methodology and cohesion of each of
                 these studies. Results: The article concludes that the
                 focus of these studies is clear, but their methodology
                 is incomplete and inadequate, their overall cohesion is
                 poor. The findings lead to the development of a design
                 framework and a set of questions for the design,
                 reporting, and review of good user studies for EUSC.
                 The detailed analysis and the insights obtained from
                 the analysis should be applicable to the design of user
                 studies for service-oriented systems as well and indeed
                 for any user studies related to software artifacts.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "15",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Chatzakou:2019:DCC,
  author =       "Despoina Chatzakou and Ilias Leontiadis and Jeremy
                 Blackburn and Emiliano {De Cristofaro} and Gianluca
                 Stringhini and Athena Vakali and Nicolas Kourtellis",
  title =        "Detecting Cyberbullying and Cyberaggression in Social
                 Media",
  journal =      j-TWEB,
  volume =       "13",
  number =       "3",
  pages =        "17:1--17:??",
  month =        oct,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3343484",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Oct 22 08:10:07 MDT 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3343484",
  abstract =     "Cyberbullying and cyberaggression are increasingly
                 worrisome phenomena affecting people across all
                 demographics. More than half of young social media
                 users worldwide have been exposed to such prolonged
                 and/or coordinated digital harassment. Victims can
                 experience a wide range of emotions, with negative
                 consequences such as embarrassment, depression,
                 isolation from other community members, which embed the
                 risk to lead to even more critical consequences, such
                 as suicide attempts. In this work, we take the first
                 concrete steps to understand the characteristics of
                 abusive behavior in Twitter, one of today's largest
                 social media platforms. We analyze 1.2 million users
                 and 2.1 million tweets, comparing users participating
                 in discussions around seemingly normal topics like the
                 NBA, to those more likely to be hate-related, such as
                 the Gamergate controversy, or the gender pay inequality
                 at the BBC station. We also explore specific
                 manifestations of abusive behavior, i.e., cyberbullying
                 and cyberaggression, in one of the hate-related
                 communities (Gamergate). We present a robust
                 methodology to distinguish bullies and aggressors from
                 normal Twitter users by considering text, user, and
                 network-based attributes. Using various
                 state-of-the-art machine-learning algorithms, we
                 classify these accounts with over 90\% accuracy and
                 AUC. Finally, we discuss the current status of Twitter
                 user accounts marked as abusive by our methodology and
                 study the performance of potential mechanisms that can
                 be used by Twitter to suspend users in the future.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "17",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Perino:2019:LTM,
  author =       "Diego Perino and Matteo Varvello and Claudio
                 Soriente",
  title =        "Long-term Measurement and Analysis of the Free Proxy
                 Ecosystem",
  journal =      j-TWEB,
  volume =       "13",
  number =       "4",
  pages =        "18:1--18:??",
  month =        dec,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3360695",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat Dec 21 07:39:03 MST 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3360695",
  abstract =     "Free web proxies promise anonymity and censorship
                 circumvention at no cost. Several websites publish
                 lists of free proxies organized by country, anonymity
                 level, and performance. These lists index hundreds of
                 thousands of hosts discovered via automated tools and
                 crowd-sourcing. A complex free proxy ecosystem has been
                 forming over the years, of which very little is known.
                 In this article, we shed light on this ecosystem via a
                 distributed measurement platform that leverages both
                 active and passive measurements. Active measurements
                 are carried out by an infrastructure we name
                 ProxyTorrent, which discovers free proxies, assesses
                 their performance, and detects potential malicious
                 activities. Passive measurements focus on proxy
                 performance and usage in the wild, and are accomplished
                 by means of a Chrome extension named Ciao. ProxyTorrent
                 has been running since January 2017, monitoring up to
                 230K free proxies. Ciao was launched in March 2017 and
                 has thus far served roughly 9.7K users and generated
                 14TB of traffic. Our analysis shows that less than 2\%
                 of the proxies announced on the Web indeed proxy
                 traffic on behalf of users; further, only half of these
                 proxies have decent performance and can be used
                 reliably. Every day, around 5\%--10\% of the active
                 proxies exhibit malicious behaviors, e.g.,
                 advertisement injection, TLS interception, and
                 cryptojacking, and these proxies are also the ones
                 providing the best performance. Through the analysis of
                 more than 14TB of proxied traffic, we show that web
                 browsing is the primary user activity. Geo-blocking
                 avoidance-allegedly a popular use case for free web
                 proxies-accounts for 30\% or less of the traffic, and
                 it mostly involves countries hosting popular
                 geo-blocked content.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "18",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Liu:2019:FPS,
  author =       "Daxin Liu and Gong Cheng and Qingxia Liu and Yuzhong
                 Qu",
  title =        "Fast and Practical Snippet Generation for {RDF}
                 Datasets",
  journal =      j-TWEB,
  volume =       "13",
  number =       "4",
  pages =        "19:1--19:??",
  month =        dec,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3365575",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat Dec 21 07:39:03 MST 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3365575",
  abstract =     "Triple-structured open data creates value in many
                 ways. However, the reuse of datasets is still
                 challenging. Users feel difficult to assess the
                 usefulness of a large dataset containing thousands or
                 millions of triples. To satisfy the needs, existing
                 abstractive methods produce a concise high-level
                 abstraction of data. Complementary to that, we adopt
                 the extractive strategy and aim to select the optimum
                 small subset of data from a dataset as a snippet to
                 compactly illustrate the content of the dataset. This
                 has been formulated as a combinatorial optimization
                 problem in our previous work. In this article, we
                 design a new algorithm for the problem, which is an
                 order of magnitude faster than the previous one but has
                 the same approximation ratio. We also develop an
                 anytime algorithm that can generate empirically better
                 solutions using additional time. To suit datasets that
                 are partially accessible via online query services
                 (e.g., SPARQL endpoints for RDF data), we adapt our
                 algorithms to trade off quality of snippet for
                 feasibility and efficiency in the Web environment. We
                 carry out extensive experiments based on real RDF
                 datasets and SPARQL endpoints for evaluating quality
                 and running time. The results demonstrate the
                 effectiveness and practicality of our proposed
                 algorithms.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "19",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Manica:2019:CUH,
  author =       "Edimar Manica and Carina Friedrich Dorneles and Renata
                 Galante",
  title =        "Combining {URL} and {HTML} Features for Entity
                 Discovery in the {Web}",
  journal =      j-TWEB,
  volume =       "13",
  number =       "4",
  pages =        "20:1--20:??",
  month =        dec,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3365574",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat Dec 21 07:39:03 MST 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/ft_gateway.cfm?id=3365574",
  abstract =     "The web is a large repository of entity-pages. An
                 entity-page is a page that publishes data representing
                 an entity of a particular type, for example, a page
                 that describes a driver on a website about a car racing
                 championship. The attribute values published in the
                 entity-pages can be used for many data-driven
                 companies, such as insurers, retailers, and search
                 engines. In this article, we define a novel method,
                 called SSUP, which discovers the entity-pages on the
                 websites. The novelty of our method is that it combines
                 URL and HTML features in a way that allows the URL
                 terms to have different weights depending on their
                 capacity to distinguish entity-pages from other pages,
                 and thus the efficacy of the entity-page discovery task
                 is increased. SSUP determines the similarity thresholds
                 on each website without human intervention. We carried
                 out experiments on a dataset with different real-world
                 websites and a wide range of entity types. SSUP
                 achieved a 95\% rate of precision and 85\% recall rate.
                 Our method was compared with two state-of-the-art
                 methods and outperformed them with a precision gain
                 between 51\% and 66\%.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "20",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Yu:2019:EPP,
  author =       "Weiren Yu and Julie McCann and Chengyuan Zhang",
  title =        "Efficient Pairwise Penetrating-rank Similarity
                 Retrieval",
  journal =      j-TWEB,
  volume =       "13",
  number =       "4",
  pages =        "21:1--21:??",
  month =        dec,
  year =         "2019",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3368616",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat Dec 21 07:39:03 MST 2019",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/pagerank.bib;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  abstract =     "Many web applications demand a measure of similarity
                 between two entities, such as collaborative filtering,
                 web document ranking, linkage prediction, and anomaly
                 detection. P-Rank (Penetrating-Rank) has been accepted
                 as a promising graph-based similarity measure, as it
                 provides a comprehensive way of encoding both incoming
                 and outgoing links into assessment. However, the
                 existing method to compute P-Rank is iterative in
                 nature and rather cost-inhibitive. Moreover, the
                 accuracy estimate and stability issues for P-Rank
                 computation have not been addressed. In this article,
                 we consider the optimization techniques for P-Rank
                 search that encompasses its accuracy, stability, and
                 computational efficiency. (1) The accuracy estimation
                 is provided for P-Rank iterations, with the aim to find
                 out the number of iterations, $k$, required to
                 guarantee a desired accuracy. (2) A rigorous bound on
                 the condition number of P-Rank is obtained for
                 stability analysis. Based on this bound, it can be
                 shown that P-Rank is stable and well-conditioned when
                 the damping factors are chosen to be suitably small.
                 (3) Two matrix-based algorithms, applicable to digraphs
                 and undirected graphs, are, respectively, devised for
                 efficient P-Rank computation, which improves the
                 computational time from $ O(k n^3) $ to $ O(\upsilon
                 n^2 + \upsilon^6) $ for digraphs, and to $ O(\upsilon
                 n^2) $ for undirected graphs, where $n$ is the number
                 of vertices in the graph, and $ \upsilon (\ll n)$ is
                 the target rank of the graph. Moreover, our proposed
                 algorithms can significantly reduce the memory space of
                 P-Rank computations from $ O(n^2) $ to $ O(\upsilon n +
                 \upsilon^4) $ for digraphs, and to $ O(\upsilon n) $
                 for undirected graphs, respectively. Finally, extensive
                 experiments on real-world and synthetic datasets
                 demonstrate the usefulness and efficiency of the
                 proposed techniques for P-Rank similarity assessment on
                 various networks.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "21",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J1062",
}

@Article{Eraslan:2020:BBW,
  author =       "Sukru Eraslan and Yeliz Yesilada and Simon Harper",
  title =        "{``The Best of Both Worlds!''}: Integration of {Web}
                 Page and Eye Tracking Data Driven Approaches for
                 Automatic {AOI} Detection",
  journal =      j-TWEB,
  volume =       "14",
  number =       "1",
  pages =        "1:1--1:31",
  month =        feb,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3372497",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat Feb 8 06:24:56 MST 2020",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/abs/10.1145/3372497",
  abstract =     "Web pages are composed of different kinds of elements
                 (menus, adverts, etc.). Segmenting pages into their
                 elements has long been important in understanding how
                 people experience those pages and in making those
                 experiences {``better.''} Many approaches have
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "1",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Shah:2020:OMA,
  author =       "Ankit Shah and Rajesh Ganesan and Sushil Jajodia and
                 Hasan Cam",
  title =        "An Outsourcing Model for Alert Analysis in a
                 Cybersecurity Operations Center",
  journal =      j-TWEB,
  volume =       "14",
  number =       "1",
  pages =        "2:1--2:22",
  month =        feb,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3372498",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat Feb 8 06:24:56 MST 2020",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/abs/10.1145/3372498",
  abstract =     "A typical Cybersecurity Operations Center (CSOC) is a
                 service organization. It hires and trains analysts,
                 whose task is to perform analysis of alerts that were
                 generated while monitoring the client's networks. Due
                 to ever-increasing financial and \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "2",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Abulaish:2020:SFL,
  author =       "Muhammad Abulaish and Ashraf Kamal and Mohammed J.
                 Zaki",
  title =        "A Survey of Figurative Language and Its Computational
                 Detection in Online Social Networks",
  journal =      j-TWEB,
  volume =       "14",
  number =       "1",
  pages =        "3:1--3:52",
  month =        feb,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3375547",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat Feb 8 06:24:56 MST 2020",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/abs/10.1145/3375547",
  abstract =     "The frequent usage of figurative language on online
                 social networks, especially on Twitter, has the
                 potential to mislead traditional sentiment analysis and
                 recommender systems. Due to the extensive use of
                 slangs, bashes, flames, and non-literal texts,
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "3",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Hassanpour:2020:IAV,
  author =       "Masoud Hassanpour and Seyed Amir Hoseinitabatabaei and
                 Payam Barnaghi and Rahim Tafazolli",
  title =        "Improving the Accuracy of the Video Popularity
                 Prediction Models through User Grouping and Video
                 Popularity Classification",
  journal =      j-TWEB,
  volume =       "14",
  number =       "1",
  pages =        "4:1--4:28",
  month =        feb,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3372499",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat Feb 8 06:24:56 MST 2020",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/abs/10.1145/3372499",
  abstract =     "This article proposes a novel approach for enhancing
                 the video popularity prediction models. Using the
                 proposed approach, we enhance three popularity
                 prediction techniques that outperform the accuracy of
                 the prior state-of-the-art solutions. The major
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "4",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Li:2020:TAS,
  author =       "Guohui Li and Qi Chen and Bolong Zheng and Nguyen Quoc
                 Viet Hung and Pan Zhou and Guanfeng Liu",
  title =        "Time-aspect-sentiment Recommendation Models Based on
                 Novel Similarity Measure Methods",
  journal =      j-TWEB,
  volume =       "14",
  number =       "2",
  pages =        "5:1--5:26",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3375548",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Apr 21 08:25:53 MDT 2020",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/abs/10.1145/3375548",
  abstract =     "The explosive growth of e-commerce has led to the
                 development of the recommendation system. The
                 recommendation system aims to provide a set of items
                 that meet users' personalized needs through analyzing
                 users' consumption records. However, the \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "5",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Carpineto:2020:ESA,
  author =       "Claudio Carpineto and Giovanni Romano",
  title =        "An Experimental Study of Automatic Detection and
                 Measurement of Counterfeit in Brand Search Results",
  journal =      j-TWEB,
  volume =       "14",
  number =       "2",
  pages =        "6:1--6:35",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3378443",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Apr 21 08:25:53 MDT 2020",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/abs/10.1145/3378443",
  abstract =     "Brand search results are poisoned by fake ecommerce
                 websites that infringe on the trademark rights of
                 legitimate holders. In this article, we study how to
                 tackle and measure this problem automatically. We
                 present a pipeline with two machine learning \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "6",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Tonge:2020:IPP,
  author =       "Ashwini Tonge and Cornelia Caragea",
  title =        "Image Privacy Prediction Using Deep Neural Networks",
  journal =      j-TWEB,
  volume =       "14",
  number =       "2",
  pages =        "7:1--7:32",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3386082",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Apr 21 08:25:53 MDT 2020",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/abs/10.1145/3386082",
  abstract =     "Images today are increasingly shared online on social
                 networking sites such as Facebook, Flickr, and
                 Instagram. Image sharing occurs not only within a group
                 of friends but also more and more outside a user's
                 social circles for purposes of social \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "7",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Laperdrix:2020:BFS,
  author =       "Pierre Laperdrix and Nataliia Bielova and Benoit
                 Baudry and Gildas Avoine",
  title =        "Browser Fingerprinting: a Survey",
  journal =      j-TWEB,
  volume =       "14",
  number =       "2",
  pages =        "8:1--8:33",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3386040",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Apr 21 08:25:53 MDT 2020",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/abs/10.1145/3386040",
  abstract =     "With this article, we survey the research performed in
                 the domain of browser fingerprinting, while providing
                 an accessible entry point to newcomers in the field. We
                 explain how this technique works and where it stems
                 from. We analyze the related work in \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "8",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Shi:2020:TAW,
  author =       "Min Shi and Yufei Tang and Xingquan Zhu and Jianxun
                 Liu",
  title =        "Topic-aware {Web} Service Representation Learning",
  journal =      j-TWEB,
  volume =       "14",
  number =       "2",
  pages =        "9:1--9:23",
  month =        apr,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3386041",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Tue Apr 21 08:25:53 MDT 2020",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/abs/10.1145/3386041",
  abstract =     "The advent of Service-Oriented Architecture (SOA) has
                 brought a fundamental shift in the way in which
                 distributed applications are implemented. An
                 overwhelming number of Web-based services (e.g., APIs
                 and Mashups) have leveraged this shift and furthered
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "9",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Xiao:2020:PRF,
  author =       "Zhijun Xiao and Cuiping Li and Hong Chen",
  title =        "{PatternRank+NN}: a Ranking Framework Bringing User
                 Behaviors into Entity Set Expansion from {Web} Search
                 Queries",
  journal =      j-TWEB,
  volume =       "14",
  number =       "3",
  pages =        "10:1--10:15",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3386042",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed Jul 22 17:29:55 MDT 2020",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/pagerank.bib;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/abs/10.1145/3386042",
  abstract =     "We propose a ranking framework, called PatternRank+NN,
                 for expanding a set of seed entities of a particular
                 class (i.e., entity set expansion) from Web search
                 queries. PatternRank+NN consists of two parts:
                 PatternRank and NN. Unlike the traditional \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "10",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Wu:2020:STI,
  author =       "Huijun Wu and Chen Wang and Richard Nock and Wei Wang
                 and Jie Yin and Kai Lu and Liming Zhu",
  title =        "{SMINT}: Toward Interpretable and Robust Model Sharing
                 for Deep Neural Networks",
  journal =      j-TWEB,
  volume =       "14",
  number =       "3",
  pages =        "11:1--11:28",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3381833",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed Jul 22 17:29:55 MDT 2020",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/abs/10.1145/3381833",
  abstract =     "Sharing a pre-trained machine learning model,
                 particularly a deep neural network via prediction APIs,
                 is becoming a common practice on machine learning as a
                 service (MLaaS) platforms nowadays. Although deep
                 neural networks (DNN) have shown remarkable \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "11",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Chattopadhyay:2020:QAA,
  author =       "Soumi Chattopadhyay and Ansuman Banerjee",
  title =        "{QoS}-aware Automatic {Web} Service Composition with
                 Multiple Objectives",
  journal =      j-TWEB,
  volume =       "14",
  number =       "3",
  pages =        "12:1--12:38",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3389147",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed Jul 22 17:29:55 MDT 2020",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/abs/10.1145/3389147",
  abstract =     "Automatic web service composition has received a
                 significant research attention in service-oriented
                 computing over decades of research. With increasing
                 number of web services, providing an end-to-end Quality
                 of Service (QoS) guarantee in responding to \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "12",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Wu:2020:SAR,
  author =       "Zhiang Wu and Changsheng Li and Jie Cao and Yong Ge",
  title =        "On Scalability of Association-rule-based
                 Recommendation: a Unified Distributed-computing
                 Framework",
  journal =      j-TWEB,
  volume =       "14",
  number =       "3",
  pages =        "13:1--13:21",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3398202",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed Jul 22 17:29:55 MDT 2020",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/abs/10.1145/3398202",
  abstract =     "The association-rule-based approach is one of the most
                 common technologies for building recommender systems
                 and it has been extensively adopted for commercial use.
                 A variety of techniques, mainly including eligible rule
                 selection and multiple rules \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "13",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Ma:2020:RTC,
  author =       "Yun Ma and Ziniu Hu and Diandian Gu and Li Zhou and
                 Qiaozhu Mei and Gang Huang and Xuanzhe Liu",
  title =        "Roaming Through the Castle Tunnels: an Empirical
                 Analysis of Inter-app Navigation of {Android} Apps",
  journal =      j-TWEB,
  volume =       "14",
  number =       "3",
  pages =        "14:1--14:24",
  month =        jul,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3395050",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed Jul 22 17:29:55 MDT 2020",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/abs/10.1145/3395050",
  abstract =     "Smartphone applications (a.k.a., apps) have become
                 indispensable in our everyday life and work. In
                 practice, accomplishing a task on smartphones may
                 require the user to navigate among various apps. Unlike
                 Web pages that are inherently interconnected \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "14",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Jeong:2020:DOW,
  author =       "Hyuk-Jin Jeong and Inchang Jeong and Soo-Mook Moon",
  title =        "Dynamic Offloading of {Web} Application Execution
                 Using Snapshot",
  journal =      j-TWEB,
  volume =       "14",
  number =       "4",
  pages =        "15:1--15:24",
  month =        sep,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3402124",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat Sep 5 18:55:05 MDT 2020",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3402124",
  abstract =     "Mobile web platforms are facing new demands for
                 emerging applications, such as machine learning or
                 augmented reality, which require significant computing
                 powers beyond that of current mobile hardware.
                 Computation offloading can accelerate these apps by
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "15",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Javed:2020:EBD,
  author =       "Amir Javed and Pete Burnap and Matthew L. Williams and
                 Omer F. Rana",
  title =        "Emotions Behind Drive-by Download Propagation on
                 {Twitter}",
  journal =      j-TWEB,
  volume =       "14",
  number =       "4",
  pages =        "16:1--16:26",
  month =        sep,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3408894",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat Sep 5 18:55:05 MDT 2020",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3408894",
  abstract =     "Twitter has emerged as one of the most popular
                 platforms to get updates on entertainment and current
                 events. However, due to its 280-character restriction
                 and automatic shortening of URLs, it is continuously
                 targeted by cybercriminals to carry out drive-.
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "16",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Mittos:2020:AGT,
  author =       "Alexandros Mittos and Savvas Zannettou and Jeremy
                 Blackburn and Emiliano {De Cristofaro}",
  title =        "Analyzing Genetic Testing Discourse on the {Web}
                 Through the Lens of {Twitter}, {Reddit}, and {4chan}",
  journal =      j-TWEB,
  volume =       "14",
  number =       "4",
  pages =        "17:1--17:38",
  month =        sep,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3404994",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat Sep 5 18:55:05 MDT 2020",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3404994",
  abstract =     "Recent progress in genomics has enabled the emergence
                 of a flourishing market for direct-to-consumer (DTC)
                 genetic testing. Companies like 23andMe and AncestryDNA
                 provide affordable health, genealogy, and ancestry
                 reports, and have already tested tens \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "17",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Zubiaga:2020:EDS,
  author =       "Arkaitz Zubiaga and Aiqi Jiang",
  title =        "Early Detection of Social Media Hoaxes at Scale",
  journal =      j-TWEB,
  volume =       "14",
  number =       "4",
  pages =        "18:1--18:23",
  month =        sep,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3407194",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat Sep 5 18:55:05 MDT 2020",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3407194",
  abstract =     "The unmoderated nature of social media enables the
                 diffusion of hoaxes, which in turn jeopardises the
                 credibility of information gathered from social media
                 platforms. Existing research on automated detection of
                 hoaxes has the limitation of using \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "18",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Mazumdar:2020:CSP,
  author =       "Pramit Mazumdar and Bidyut Kr. Patra and Korra Sathya
                 Babu",
  title =        "Cold-start Point-of-interest Recommendation through
                 Crowdsourcing",
  journal =      j-TWEB,
  volume =       "14",
  number =       "4",
  pages =        "19:1--19:36",
  month =        sep,
  year =         "2020",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3407182",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat Sep 5 18:55:05 MDT 2020",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3407182",
  abstract =     "Recommender system is a popular tool that aims to
                 provide personalized suggestions to user about items,
                 products, services, and so on. Recommender system has
                 effectively been used in online social networks,
                 especially the location-based social networks
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "19",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Cao:2021:CCB,
  author =       "Jian Cao and Tingjie Jia and Shiyou Qian and Haiyan
                 Zhao and Jie Wang",
  title =        "{CBPCS}: a Cache-block-based Service Process Caching
                 Strategy to Accelerate the Execution of Service
                 Processes",
  journal =      j-TWEB,
  volume =       "15",
  number =       "1",
  pages =        "1:1--1:29",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3411494",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat May 22 08:52:18 MDT 2021",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3411494",
  abstract =     "With the development of cloud computing and the advent
                 of the Web 2.0 era, composing a set of Web services as
                 a service process is becoming a common practice to
                 provide more functional services. However, a service
                 process involves multiple service \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "1",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Vidyapu:2021:IMW,
  author =       "Sandeep Vidyapu and Vijaya Saradhi Vedula and Samit
                 Bhattacharya",
  title =        "Investigating and Modeling the {Web} Elements' Visual
                 Feature Influence on Free-viewing Attention",
  journal =      j-TWEB,
  volume =       "15",
  number =       "1",
  pages =        "2:1--2:27",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3409474",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat May 22 08:52:18 MDT 2021",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3409474",
  abstract =     "User attentional analyses on web elements help in
                 synthesis and rendering of webpages. However, majority
                 of the existing analyses are limited in incorporating
                 the intrinsic visual features of text and images. This
                 study aimed to analyze the influence of \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "2",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Chen:2021:DVE,
  author =       "Xu Chen and Jiangchao Yao and Maosen Li and Ya Zhang
                 and Yanfeng Wang",
  title =        "Decoupled Variational Embedding for Signed Directed
                 Networks",
  journal =      j-TWEB,
  volume =       "15",
  number =       "1",
  pages =        "3:1--3:31",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3408298",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat May 22 08:52:18 MDT 2021",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3408298",
  abstract =     "Node representation learning for signed directed
                 networks has received considerable attention in many
                 real-world applications such as link sign prediction,
                 node classification, and node recommendation. The
                 challenge lies in how to adequately encode the
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "3",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Wang:2021:ACN,
  author =       "Wei Wang and Jiaying Liu and Tao Tang and Suppawong
                 Tuarob and Feng Xia and Zhiguo Gong and Irwin King",
  title =        "Attributed Collaboration Network Embedding for
                 Academic Relationship Mining",
  journal =      j-TWEB,
  volume =       "15",
  number =       "1",
  pages =        "4:1--4:20",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3409736",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat May 22 08:52:18 MDT 2021",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3409736",
  abstract =     "Finding both efficient and effective quantitative
                 representations for scholars in scientific digital
                 libraries has been a focal point of research. The
                 unprecedented amounts of scholarly datasets, combined
                 with contemporary machine learning and big data
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "4",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Bailey:2021:SLA,
  author =       "Shawn Bailey and Yue Zhang and Arti Ramesh and
                 Jennifer Golbeck and Lise Getoor",
  title =        "A Structured and Linguistic Approach to Understanding
                 Recovery and Relapse in {AA}",
  journal =      j-TWEB,
  volume =       "15",
  number =       "1",
  pages =        "5:1--5:35",
  month =        jan,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3423208",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat May 22 08:52:18 MDT 2021",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3423208",
  abstract =     "Alcoholism, also known as Alcohol Use Disorder (AUD),
                 is a serious problem affecting millions of people
                 worldwide. Recovery from AUD is known to be challenging
                 and often leads to relapse at various points after
                 enrolling in a rehabilitation program such \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "5",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Gong:2021:CSP,
  author =       "Qingyuan Gong and Yang Chen and Xinlei He and Yu Xiao
                 and Pan Hui and Xin Wang and Xiaoming Fu",
  title =        "Cross-site Prediction on Social Influence for
                 Cold-start Users in Online Social Networks",
  journal =      j-TWEB,
  volume =       "15",
  number =       "2",
  pages =        "6:1--6:23",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3409108",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat May 22 08:52:19 MDT 2021",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3409108",
  abstract =     "Online social networks (OSNs) have become a commodity
                 in our daily life. As an important concept in sociology
                 and viral marketing, the study of social influence has
                 received a lot of attentions in academia. Most of the
                 existing proposals work well on \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "6",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Alhosban:2021:TPS,
  author =       "Amal Alhosban and Zaki Malik and Khayyam Hashmi and
                 Brahim Medjahed and Hassan Al-Ababneh",
  title =        "A Two Phases Self-healing Framework for
                 Service-oriented Systems",
  journal =      j-TWEB,
  volume =       "15",
  number =       "2",
  pages =        "7:1--7:25",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3450443",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat May 22 08:52:19 MDT 2021",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3450443",
  abstract =     "Service-Oriented Architectures (SOA) enable the
                 automatic creation of business applications from
                 independently developed and deployed Web services. As
                 Web services are inherently a priori unknown, how to
                 deliver reliable Web services compositions is a
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "7",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Flores:2021:UWT,
  author =       "Marcel Flores and Andrew Kahn and Marc Warrior and
                 Alan Mislove and Aleksandar Kuzmanovic",
  title =        "Utilizing {Web} Trackers for {Sybil} Defense",
  journal =      j-TWEB,
  volume =       "15",
  number =       "2",
  pages =        "8:1--8:19",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3450444",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat May 22 08:52:19 MDT 2021",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3450444",
  abstract =     "User tracking has become ubiquitous practice on the
                 Web, allowing services to recommend behaviorally
                 targeted content to users. In this article, we design
                 Alibi, a system that utilizes such readily available
                 personalized content, generated by \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "8",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Roy:2021:IAI,
  author =       "Soumyadeep Roy and Shamik Sural and Niyati Chhaya and
                 Anandhavelu Natarajan and Niloy Ganguly",
  title =        "An Integrated Approach for Improving Brand Consistency
                 of {Web} Content: Modeling, Analysis, and
                 Recommendation",
  journal =      j-TWEB,
  volume =       "15",
  number =       "2",
  pages =        "9:1--9:25",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3450445",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat May 22 08:52:19 MDT 2021",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3450445",
  abstract =     "A consumer-dependent (business-to-consumer)
                 organization tends to present itself as possessing a
                 set of human qualities, which is termed the brand
                 personality of the company. The perception is impressed
                 upon the consumer through the content, be it in
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "9",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Zhang:2021:EWD,
  author =       "Jifeng Zhang and Wenjun Jiang and Jinrui Zhang and Jie
                 Wu and Guojun Wang",
  title =        "Exploring Weather Data to Predict Activity Attendance
                 in Event-based Social Network: From the Organizer's
                 View",
  journal =      j-TWEB,
  volume =       "15",
  number =       "2",
  pages =        "10:1--10:25",
  month =        may,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3440134",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat May 22 08:52:19 MDT 2021",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3440134",
  abstract =     "Event-based social networks (EBSNs) connect online and
                 offline lives. They allow online users with similar
                 interests to get together in real life. Attendance
                 prediction for activities in EBSNs has attracted a lot
                 of attention and several factors have \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "10",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{White:2021:WMN,
  author =       "Ryen W. White",
  title =        "Welcome Message from the New {Editor-in-Chief}",
  journal =      j-TWEB,
  volume =       "15",
  number =       "3",
  pages =        "11e:1--11e:1",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3456294",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jul 15 07:11:18 MDT 2021",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3456294",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "11e",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Zhang:2021:STR,
  author =       "Shuo Zhang and Krisztian Balog",
  title =        "Semantic Table Retrieval Using Keyword and Table
                 Queries",
  journal =      j-TWEB,
  volume =       "15",
  number =       "3",
  pages =        "11:1--11:33",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3441690",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jul 15 07:11:18 MDT 2021",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3441690",
  abstract =     "Tables on the Web contain a vast amount of knowledge
                 in a structured form. To tap into this valuable
                 resource, we address the problem of table retrieval:
                 answering an information need with a ranked list of
                 tables. We investigate this problem in two \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "11",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Boschi:2021:WLW,
  author =       "Gioia Boschi and Anthony P. Young and Sagar Joglekar
                 and Chiara Cammarota and Nishanth Sastry",
  title =        "Who Has the Last Word? {Understanding} How to Sample
                 Online Discussions",
  journal =      j-TWEB,
  volume =       "15",
  number =       "3",
  pages =        "12:1--12:25",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3452936",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jul 15 07:11:18 MDT 2021",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3452936",
  abstract =     "In online debates, as in offline ones, individual
                 utterances or arguments support or attack each other,
                 leading to some subset of arguments (potentially from
                 different sides of the debate) being considered more
                 relevant than others. However, online \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "12",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Jiang:2021:RSG,
  author =       "Wenjun Jiang and Jing Chen and Xiaofei Ding and Jie Wu
                 and Jiawei He and Guojun Wang",
  title =        "Review Summary Generation in Online Systems:
                 Frameworks for Supervised and Unsupervised Scenarios",
  journal =      j-TWEB,
  volume =       "15",
  number =       "3",
  pages =        "13:1--13:33",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3448015",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jul 15 07:11:18 MDT 2021",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3448015",
  abstract =     "In online systems, including e-commerce platforms,
                 many users resort to the reviews or comments generated
                 by previous consumers for decision making, while their
                 time is limited to deal with many reviews. Therefore, a
                 review summary, which contains all \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "13",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Chelmis:2021:DIC,
  author =       "Charalampos Chelmis and Daphney-Stavroula Zois",
  title =        "Dynamic, Incremental, and Continuous Detection of
                 Cyberbullying in Online Social Media",
  journal =      j-TWEB,
  volume =       "15",
  number =       "3",
  pages =        "14:1--14:33",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3448014",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jul 15 07:11:18 MDT 2021",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3448014",
  abstract =     "The potentially detrimental effects of cyberbullying
                 have led to the development of numerous automated,
                 data-driven approaches, with emphasis on classification
                 accuracy. Cyberbullying, as a form of abusive online
                 behavior, although not well-defined, is a \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "14",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Mistry:2021:SLB,
  author =       "Sajib Mistry and Sheik Mohammad Mostakim Fattah and
                 Athman Bouguettaya",
  title =        "Sequential Learning-based {IaaS} Composition",
  journal =      j-TWEB,
  volume =       "15",
  number =       "3",
  pages =        "15:1--15:37",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3452332",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jul 15 07:11:18 MDT 2021",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3452332",
  abstract =     "We propose a novel Infrastructure-as-a-Service
                 composition framework that selects an optimal set of
                 consumer requests according to the provider's
                 qualitative preferences on long-term service
                 provisions. Decision variables are included in the
                 temporal \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "15",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Zhang:2021:SUC,
  author =       "Peng Zhang and Baoxi Liu and Xianghua Ding and Tun Lu
                 and Hansu Gu and Ning Gu",
  title =        "Studying and Understanding Characteristics of
                 Post-Syncing Practice and Goal in Social Network
                 Sites",
  journal =      j-TWEB,
  volume =       "15",
  number =       "4",
  pages =        "16:1--16:26",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3457986",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jul 15 07:11:19 MDT 2021",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3457986",
  abstract =     "Many popular social network sites (SNSs) provide the
                 post-syncing functionality, which allows users to
                 synchronize posts automatically among different SNSs.
                 Nowadays there exists divergence on this functionality
                 from the view of sink SNS. The key to \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "16",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Parikh:2021:CSM,
  author =       "Pulkit Parikh and Harika Abburi and Niyati Chhaya and
                 Manish Gupta and Vasudeva Varma",
  title =        "Categorizing Sexism and Misogyny through Neural
                 Approaches",
  journal =      j-TWEB,
  volume =       "15",
  number =       "4",
  pages =        "17:1--17:31",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3457189",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jul 15 07:11:19 MDT 2021",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3457189",
  abstract =     "Sexism, an injustice that subjects women and girls to
                 enormous suffering, manifests in blatant as well as
                 subtle ways. In the wake of growing documentation of
                 experiences of sexism on the web, the automatic
                 categorization of accounts of sexism has the \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "17",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Jiao:2021:SGM,
  author =       "Simiao Jiao and Zihui Xue and Xiaowei Chen and Yuedong
                 Xu",
  title =        "Sampling Graphlets of Multiplex Networks: a Restricted
                 Random Walk Approach",
  journal =      j-TWEB,
  volume =       "15",
  number =       "4",
  pages =        "18:1--18:31",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3456291",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jul 15 07:11:19 MDT 2021",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3456291",
  abstract =     "Graphlets are induced subgraph patterns that are
                 crucial to the understanding of the structure and
                 function of a large network. A lot of effort has been
                 devoted to calculating graphlet statistics where random
                 walk-based approaches are commonly used to \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "18",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Wang:2021:IEA,
  author =       "Huan Wang and Chunming Qiao and Xuan Guo and Lei Fang
                 and Ying Sha and Zhiguo Gong",
  title =        "Identifying and Evaluating Anomalous Structural
                 Change-based Nodes in Generalized Dynamic Social
                 Networks",
  journal =      j-TWEB,
  volume =       "15",
  number =       "4",
  pages =        "19:1--19:22",
  month =        jul,
  year =         "2021",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3457906",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Thu Jul 15 07:11:19 MDT 2021",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3457906",
  abstract =     "Recently, dynamic social network research has
                 attracted a great amount of attention, especially in
                 the area of anomaly analysis that analyzes the
                 anomalous change in the evolution of dynamic social
                 networks. However, most of the current research focused
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "19",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Liu:2022:FHU,
  author =       "Bang Liu and Hanlin Zhang and Linglong Kong and Di
                 Niu",
  title =        "Factorizing Historical User Actions for Next-Day
                 Purchase Prediction",
  journal =      j-TWEB,
  volume =       "16",
  number =       "1",
  pages =        "1:1--1:26",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3468227",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Jan 7 08:00:15 MST 2022",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3468227",
  abstract =     "It is common practice for many large e-commerce
                 operators to analyze daily logged transaction data to
                 predict customer purchase behavior, which may
                 potentially lead to more effective recommendations and
                 increased sales. Traditional recommendation \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "1",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Zhao:2022:CAD,
  author =       "Yiji Zhao and Youfang Lin and Zhihao Wu and Yang Wang
                 and Haomin Wen",
  title =        "Context-aware Distance Measures for Dynamic Networks",
  journal =      j-TWEB,
  volume =       "16",
  number =       "1",
  pages =        "2:1--2:34",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3476228",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Jan 7 08:00:15 MST 2022",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3476228",
  abstract =     "Dynamic networks are widely used in the social,
                 physical, and biological sciences as a concise
                 mathematical representation of the evolving
                 interactions in dynamic complex systems. Measuring
                 distances between network snapshots is important for
                 analyzing \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "2",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Crichton:2022:HDH,
  author =       "Kyle Crichton and Nicolas Christin and Lorrie Faith
                 Cranor",
  title =        "How Do Home Computer Users Browse the Web?",
  journal =      j-TWEB,
  volume =       "16",
  number =       "1",
  pages =        "3:1--3:27",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3473343",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Jan 7 08:00:15 MST 2022",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3473343",
  abstract =     "With the ubiquity of web tracking, information on how
                 people navigate the internet is abundantly collected
                 yet, due to its proprietary nature, rarely distributed.
                 As a result, our understanding of user browsing
                 primarily derives from small-scale studies \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "3",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Andriamilanto:2022:LSE,
  author =       "Nampoina Andriamilanto and Tristan Allard and
                 Ga{\"e}tan {Le Guelvouit} and Alexandre Garel",
  title =        "A Large-scale Empirical Analysis of Browser
                 Fingerprints Properties for Web Authentication",
  journal =      j-TWEB,
  volume =       "16",
  number =       "1",
  pages =        "4:1--4:62",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3478026",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Jan 7 08:00:15 MST 2022",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3478026",
  abstract =     "Modern browsers give access to several attributes that
                 can be collected to form a browser fingerprint.
                 Although browser fingerprints have primarily been
                 studied as a web tracking tool, they can contribute to
                 improve the current state of web security by \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "4",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Poiitis:2022:ADM,
  author =       "Marinos Poiitis and Athena Vakali and Nicolas
                 Kourtellis",
  title =        "On the Aggression Diffusion Modeling and Minimization
                 in {Twitter}",
  journal =      j-TWEB,
  volume =       "16",
  number =       "1",
  pages =        "5:1--5:24",
  month =        feb,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3486218",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Jan 7 08:00:15 MST 2022",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3486218",
  abstract =     "Aggression in online social networks has been studied
                 mostly from the perspective of machine learning, which
                 detects such behavior in a static context. However, the
                 way aggression diffuses in the network has received
                 little attention as it embeds modeling \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "5",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Nelson:2022:QCT,
  author =       "Michael Nelson and Sridhar Radhakrishnan and Chandra
                 Sekharan and Amlan Chatterjee and Sudhindra Gopal
                 Krishna",
  title =        "Queryable Compression on Time-evolving {Web} and
                 Social Networks with Streaming",
  journal =      j-TWEB,
  volume =       "16",
  number =       "2",
  pages =        "6:1--6:21",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3495012",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat May 21 12:32:34 MDT 2022",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3495012",
  abstract =     "Time-evolving web and social network graphs are
                 modeled as a set of pages/individuals (nodes) and their
                 arcs (links/relationships) that change over time. Due
                 to their popularity, they have become increasingly
                 massive in terms of their number of nodes, \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "6",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Wang:2022:LSE,
  author =       "Kai Wang and Jun Pang and Dingjie Chen and Yu Zhao and
                 Dapeng Huang and Chen Chen and Weili Han",
  title =        "A Large-scale Empirical Analysis of Ransomware
                 Activities in Bitcoin",
  journal =      j-TWEB,
  volume =       "16",
  number =       "2",
  pages =        "7:1--7:29",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3494557",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat May 21 12:32:34 MDT 2022",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/bitcoin.bib;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3494557",
  abstract =     "Exploiting the anonymous mechanism of Bitcoin,
                 ransomware activities demanding ransom in bitcoins have
                 become rampant in recent years. Several existing
                 studies quantify the impact of ransomware activities,
                 mostly focusing on the amount of ransom. However,
                 victims' reactions in Bitcoin that can well reflect the
                 impact of ransomware activities are somehow largely
                 neglected. Besides, existing studies track ransom
                 transfers at the Bitcoin address level, making it
                 difficult for them to uncover the patterns of ransom
                 transfers from a macro perspective beyond Bitcoin
                 addresses.\par

                 In this article, we conduct a large-scale analysis of
                 ransom payments, ransom transfers, and victim
                 migrations in Bitcoin from 2012 to 2021. First, we
                 develop a fine-grained address clustering method to
                 cluster Bitcoin addresses into users, which enables us
                 to identify more addresses controlled by ransomware
                 criminals. Second, motivated by the fact that Bitcoin
                 activities and their participants already formed stable
                 industries, such as Darknet and Miner, we train a
                 multi-label classification model to identify the
                 industry identifiers of users. Third, we identify
                 ransom payment transactions and then quantify the
                 amount of ransom and the number of victims in 63
                 ransomware activities. Finally, after we analyze the
                 trajectories of ransom transferred across different
                 industries and track victims' migrations across
                 industries, we find out that to obscure the purposes of
                 their transfer trajectories, most ransomware criminals
                 (e.g., operators of Locky and Wannacry) prefer to
                 spread ransom into multiple industries instead of
                 utilizing the services of Bitcoin mixers. Compared with
                 other industries, Investment is highly resilient to
                 ransomware activities in the sense that the number of
                 users in Investment remains relatively stable.
                 Moreover, we also observe that a few victims become
                 active in the Darknet after paying ransom. Our findings
                 in this work can help authorities deeply understand
                 ransomware activities in Bitcoin. While our study
                 focuses on ransomware, our methods are potentially
                 applicable to other cybercriminal activities that have
                 similarly adopted bitcoins as their payments.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "7",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Biswas:2022:TFR,
  author =       "Arpita Biswas and Gourab K. Patro and Niloy Ganguly
                 and Krishna P. Gummadi and Abhijnan Chakraborty",
  title =        "Toward Fair Recommendation in Two-sided Platforms",
  journal =      j-TWEB,
  volume =       "16",
  number =       "2",
  pages =        "8:1--8:34",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3503624",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat May 21 12:32:34 MDT 2022",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3503624",
  abstract =     "Many online platforms today (such as Amazon, Netflix,
                 Spotify, LinkedIn, and AirBnB) can be thought of as
                 two-sided markets with producers and customers of goods
                 and services. Traditionally, recommendation services in
                 these platforms have focused on \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "8",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Magno:2022:MIO,
  author =       "Gabriel Magno and Virgilio Almeida",
  title =        "Measuring International Online Human Values with Word
                 Embeddings",
  journal =      j-TWEB,
  volume =       "16",
  number =       "2",
  pages =        "9:1--9:38",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3501306",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat May 21 12:32:34 MDT 2022",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3501306",
  abstract =     "As the Internet grows in number of users and in the
                 diversity of services, it becomes more influential on
                 peoples lives. It has the potential of constructing or
                 modifying the opinion, the mental perception, and the
                 values of individuals. What is being \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "9",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Karanatsiou:2022:MTB,
  author =       "Dimitra Karanatsiou and Pavlos Sermpezis and Dritjon
                 Gruda and Konstantinos Kafetsios and Ilias Dimitriadis
                 and Athena Vakali",
  title =        "My Tweets Bring All the Traits to the Yard: Predicting
                 Personality and Relational Traits in Online Social
                 Networks",
  journal =      j-TWEB,
  volume =       "16",
  number =       "2",
  pages =        "10:1--10:26",
  month =        may,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3523749",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat May 21 12:32:34 MDT 2022",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3523749",
  abstract =     "Users in Online Social Networks (OSNs,) leave traces
                 that reflect their personality characteristics. The
                 study of these traces is important for several fields,
                 such as social science, psychology, marketing, and
                 others. Despite a marked increase in \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "10",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Qian:2022:PVR,
  author =       "Xin Qian and Ryan A. Rossi and Fan Du and Sungchul Kim
                 and Eunyee Koh and Sana Malik and Tak Yeon Lee and
                 Nesreen K. Ahmed",
  title =        "Personalized Visualization Recommendation",
  journal =      j-TWEB,
  volume =       "16",
  number =       "3",
  pages =        "11:1--11:??",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3538703",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed Nov 16 08:39:27 MST 2022",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3538703",
  abstract =     "Visualization recommendation work has focused solely
                 on scoring visualizations based on the underlying
                 dataset, and not the actual user and their past
                 visualization feedback. These systems recommend the
                 same visualizations for every user, despite that the
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "11",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Raponi:2022:FNP,
  author =       "Simone Raponi and Zeinab Khalifa and Gabriele Oligeri
                 and Roberto {Di Pietro}",
  title =        "Fake News Propagation: a Review of Epidemic Models,
                 Datasets, and Insights",
  journal =      j-TWEB,
  volume =       "16",
  number =       "3",
  pages =        "12:1--12:??",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3522756",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed Nov 16 08:39:27 MST 2022",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3522756",
  abstract =     "Fake news propagation is a complex phenomenon
                 influenced by a multitude of factors whose
                 identification and impact assessment is challenging.
                 Although many models have been proposed in the
                 literature, the one capturing all the properties of a
                 real fake-. \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "12",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Squicciarini:2022:EUG,
  author =       "Anna Squicciarini and Sarah Rajtmajer and Yang Gao and
                 Justin Semonsen and Andrew Belmonte and Pratik
                 Agarwal",
  title =        "An Extended Ultimatum Game for Multi-Party Access
                 Control in Social Networks",
  journal =      j-TWEB,
  volume =       "16",
  number =       "3",
  pages =        "13:1--13:??",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3555351",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed Nov 16 08:39:27 MST 2022",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3555351",
  abstract =     "In this article, we aim to answer an important set of
                 questions about the potential longitudinal effects of
                 repeated sharing and privacy settings decisions over
                 jointly managed content among users in a social
                 network. We model user interactions through a
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "13",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Oswald:2022:SIA,
  author =       "C. Oswald and Sona Elza Simon and Arnab Bhattacharya",
  title =        "{SpotSpam}: Intention Analysis-driven {SMS} Spam
                 Detection Using {BERT} Embeddings",
  journal =      j-TWEB,
  volume =       "16",
  number =       "3",
  pages =        "14:1--14:??",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3538491",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed Nov 16 08:39:27 MST 2022",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3538491",
  abstract =     "Short Message Service (SMS) is one of the widely used
                 mobile applications for global communication for
                 personal and business purposes. Its widespread use for
                 customer interaction, business updates, and reminders
                 has made it a billion-dollar industry in \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "14",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Jha:2022:IPP,
  author =       "Nikhil Jha and Martino Trevisan and Luca Vassio and
                 Marco Mellia",
  title =        "The {Internet} with Privacy Policies: Measuring The
                 {Web} Upon Consent",
  journal =      j-TWEB,
  volume =       "16",
  number =       "3",
  pages =        "15:1--15:??",
  month =        aug,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3555352",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Wed Nov 16 08:39:27 MST 2022",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3555352",
  abstract =     "To protect user privacy, legislators have regulated
                 the use of tracking technologies, mandating the
                 acquisition of users' consent before collecting data.
                 As a result, websites started showing more and more
                 consent management modules-i.e., Consent Banners-.
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "15",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Frosini:2022:OTF,
  author =       "Riccardo Frosini and Alexandra Poulovassilis and Peter
                 T. Wood and Andrea Cal{\'\i}",
  title =        "Optimisation Techniques for Flexible {SPARQL}
                 Queries",
  journal =      j-TWEB,
  volume =       "16",
  number =       "4",
  pages =        "16:1--16:??",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3532855",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Dec 9 06:51:15 MST 2022",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3532855",
  abstract =     "Resource Description Framework datasets can be queried
                 using the SPARQL language but are often irregularly
                 structured and incomplete, which may make precise query
                 formulation hard for users. The SPARQL$^{AR}$ language
                 extends SPARQL 1.1 with two operators-\ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "16",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Chaqfeh:2022:JWD,
  author =       "Moumena Chaqfeh and Russell Coke and Jacinta Hu and
                 Waleed Hashmi and Lakshmi Subramanian and Talal Rahwan
                 and Yasir Zaki",
  title =        "\pkg{JSAnalyzer}: a {Web} Developer Tool for
                 Simplifying Mobile {Web} Pages through Non-critical
                 {JavaScript} Elimination",
  journal =      j-TWEB,
  volume =       "16",
  number =       "4",
  pages =        "17:1--17:??",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3550358",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Dec 9 06:51:15 MST 2022",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/java2020.bib;
                 http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3550358",
  abstract =     "The amount of JavaScript used in web pages has
                 substantially grown in the past decade, leading to
                 large and complex pages that are computationally
                 intensive for handheld mobile devices. Due to the
                 increasing usage of these devices to access today's
                 web, \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "17",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Upadhyaya:2022:SFV,
  author =       "Apoorva Upadhyaya and Joydeep Chandra",
  title =        "Spotting Flares: The Vital Signs of the Viral Spread
                 of Tweets Made During Communal Incidents",
  journal =      j-TWEB,
  volume =       "16",
  number =       "4",
  pages =        "18:1--18:??",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3550357",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Dec 9 06:51:15 MST 2022",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3550357",
  abstract =     "With the increasing use of Twitter for encouraging
                 users to instigate violent behavior with hate and
                 racial content, it becomes necessary to investigate the
                 uniqueness in the dynamics of the spread of tweets made
                 during violent communal incidents and the \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "18",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Chen:2022:DAC,
  author =       "Qi Chen and Guohui Li and Quan Zhou and Si Shi and
                 Deqing Zou",
  title =        "Double Attention Convolutional Neural Network for
                 Sequential Recommendation",
  journal =      j-TWEB,
  volume =       "16",
  number =       "4",
  pages =        "19:1--19:??",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3555350",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Dec 9 06:51:15 MST 2022",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3555350",
  abstract =     "The explosive growth of e-commerce and online service
                 has led to the development of recommender system.
                 Aiming to provide a list of items to meet a user's
                 personalized need by analyzing his/her interaction $^1$
                 history, recommender system has been widely \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "19",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Wang:2022:BBS,
  author =       "Xi Wang and Iadh Ounis and Craig Macdonald",
  title =        "\pkg{BanditProp}: Bandit Selection of Review
                 Properties for Effective Recommendation",
  journal =      j-TWEB,
  volume =       "16",
  number =       "4",
  pages =        "20:1--20:??",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3532859",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Dec 9 06:51:15 MST 2022",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3532859",
  abstract =     "Many recent recommendation systems leverage the large
                 quantity of reviews placed by users on items. However,
                 it is both challenging and important to accurately
                 measure the usefulness of such reviews for effective
                 recommendation. In particular, users have \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "20",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Moon:2022:MME,
  author =       "Taegeun Moon and Hyoungshick Kim and Sangwon Hyun",
  title =        "\pkg{Mutexion}: Mutually Exclusive Compression System
                 for Mitigating Compression Side-Channel Attacks",
  journal =      j-TWEB,
  volume =       "16",
  number =       "4",
  pages =        "21:1--21:??",
  month =        nov,
  year =         "2022",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3532850",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Fri Dec 9 06:51:15 MST 2022",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3532850",
  abstract =     "To enhance the performance of web services, web
                 servers often compress data to be delivered.
                 Unfortunately, the data compression technique has also
                 introduced a side effect called compression
                 side-channel attacks (CSCA). CSCA allows eavesdroppers
                 to \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "21",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Haider:2023:CLV,
  author =       "Waqar Haider and Yeliz Yesilada",
  title =        "Classification of Layout vs. Relational Tables on the
                 {Web}: Machine Learning with Rendered Pages",
  journal =      j-TWEB,
  volume =       "17",
  number =       "1",
  pages =        "1:1--1:??",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3555349",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 17 18:10:44 MDT 2023",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3555349",
  abstract =     "Table mining on the web is an open problem, and none
                 of the previously proposed techniques provides a
                 complete solution. Most research focuses on the
                 structure of the HTML document, but because of the
                 nature and structure of the web, it is still a
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "1",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Xiao:2023:DKE,
  author =       "Yunming Xiao and Matteo Varvello and Marc Warrior and
                 Aleksandar Kuzmanovic",
  title =        "Decoding the {Kodi} Ecosystem",
  journal =      j-TWEB,
  volume =       "17",
  number =       "1",
  pages =        "2:1--2:??",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3563700",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 17 18:10:44 MDT 2023",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3563700",
  abstract =     "Free and open-source media centers are experiencing a
                 boom in popularity for the convenience they offer users
                 seeking to remotely consume digital content. Kodi is
                 today's most popular home media center, with millions
                 of users worldwide. Kodi's popularity derives from its
                 ability to centralize the sheer amount of media content
                 available on the Web, both free and copyrighted.
                 Researchers have been hinting at potential security
                 concerns around Kodi, due to add-ons injecting unwanted
                 content as well as user settings linked with security
                 holes. Motivated by these observations, this article
                 conducts the first comprehensive analysis of the Kodi
                 ecosystem: 15,000 Kodi users from 104 countries, 11,000
                 unique add-ons, and data collected over 9 months.

                 Our work makes three important contributions. Our first
                 contribution is that we build ``crawling'' software
                 (de-Kodi) which can automatically install a Kodi
                 add-on, explore its menu, and locate (video) content.
                 This is challenging for two main reasons. First, Kodi
                 largely relies on visual information and user input
                 which intrinsically complicates automation. Second, the
                 potential sheer size of this ecosystem (i.e., the
                 number of available add-ons) requires a highly scalable
                 crawling solution. Our second contribution is that we
                 develop a solution to discover Kodi add-ons. Our
                 solution combines Web crawling of popular websites
                 where Kodi add-ons are published (LazyKodi and GitHub)
                 and SafeKodi, a Kodi add-on we have developed which
                 leverages the help of Kodi users to learn which add-ons
                 are used in the wild and, in return, offers information
                 about how safe these add-ons are, e.g., do they track
                 user activity or contact sketchy URLs/IP addresses. Our
                 third contribution is a classifier to passively detect
                 Kodi traffic and add-on usage in the wild.

                 Our analysis of the Kodi ecosystem reveals the
                 following findings. We find that most installed add-ons
                 are unofficial but safe to use. Still, 78\% of the
                 users have installed at least one unsafe add-on, and
                 even worse, such add-ons are among the most popular. In
                 response to the information offered by SafeKodi,
                 one-third of the users reacted by disabling some of
                 their add-ons. However, the majority of users ignored
                 our warnings for several months attracted by the
                 content such unsafe add-ons have to offer. Last but not
                 least, we show that Kodi's auto-update, a feature
                 active for 97.6\% of SafeKodi users, makes Kodi users
                 easily identifiable by their ISPs. While passively
                 identifying which Kodi add-on is in use is, as
                 expected, much harder, we also find that many
                 unofficial add-ons do not use HTTPS yet, making their
                 passive detection straightforward.",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "2",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Wang:2023:CPS,
  author =       "Xiao Wang and Craig MacDonald and Nicola Tonellotto
                 and Iadh Ounis",
  title =        "{ColBERT-PRF}: Semantic Pseudo-Relevance Feedback for
                 Dense Passage and Document Retrieval",
  journal =      j-TWEB,
  volume =       "17",
  number =       "1",
  pages =        "3:1--3:??",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3572405",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 17 18:10:44 MDT 2023",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3572405",
  abstract =     "Pseudo-relevance feedback mechanisms, from Rocchio to
                 the relevance models, have shown the usefulness of
                 expanding and reweighting the users' initial queries
                 using information occurring in an initial set of
                 retrieved documents, known as the pseudo-. \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "3",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Zou:2023:PTL,
  author =       "Lixin Zou and Weixue Lu and Yiding Liu and Hengyi Cai
                 and Xiaokai Chu and Dehong Ma and Daiting Shi and Yu
                 Sun and Zhicong Cheng and Simiu Gu and Shuaiqiang Wang
                 and Dawei Yin",
  title =        "Pre-trained Language Model-based Retrieval and Ranking
                 for {Web} Search",
  journal =      j-TWEB,
  volume =       "17",
  number =       "1",
  pages =        "4:1--4:??",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3568681",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 17 18:10:44 MDT 2023",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3568681",
  abstract =     "Pre-trained language representation models (PLMs) such
                 as BERT and Enhanced Representation through kNowledge
                 IntEgration (ERNIE) have been integral to achieving
                 recent improvements on various downstream tasks,
                 including information retrieval. However, it \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "4",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Chen:2023:KED,
  author =       "Lei Chen and Jie Cao and Weichao Liang and Jia Wu and
                 Qiaolin Ye",
  title =        "Keywords-enhanced Deep Reinforcement Learning Model
                 for Travel Recommendation",
  journal =      j-TWEB,
  volume =       "17",
  number =       "1",
  pages =        "5:1--5:??",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3570959",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 17 18:10:44 MDT 2023",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3570959",
  abstract =     "Tourism is an important industry and a popular
                 entertainment activity involving billions of visitors
                 per annum. One challenging problem tourists face is
                 identifying satisfactory products from vast tourism
                 information. Most of travel recommendation methods
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "5",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Wang:2023:ECR,
  author =       "Yingxu Wang and Xiaoru Chen and Jinyuan Fang and
                 Zaiqiao Meng and Shangsong Liang",
  title =        "Enhancing Conversational Recommendation Systems with
                 Representation Fusion",
  journal =      j-TWEB,
  volume =       "17",
  number =       "1",
  pages =        "6:1--6:??",
  month =        feb,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3577034",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 17 18:10:44 MDT 2023",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3577034",
  abstract =     "Conversational Recommendation Systems (CRSs) aim to
                 improve recommendation performance by utilizing
                 information from a conversation session. A CRS first
                 constructs questions and then asks users for their
                 feedback in each conversation session to refine
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "6",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Chen:2023:FWO,
  author =       "Chung-Chi Chen and Hen-Hsen Huang and Hiroya Takamura
                 and Makoto P. Kato and Yu-Lieh Huang",
  title =        "{FinTech} on the {Web}: an Overview",
  journal =      j-TWEB,
  volume =       "17",
  number =       "2",
  pages =        "7:1--7:??",
  month =        may,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3572404",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 17 18:10:45 MDT 2023",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3572404",
  abstract =     "In this article, we provide an overview of ACM TWEB's
                 special issue, Financial Technology on the Web. This
                 special issue covers diverse topics: (1) a new
                 architecture for leveraging online news to investment
                 and risk management, (2) a cross-platform \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "7",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Ang:2023:IRM,
  author =       "Gary Ang and Ee-Peng Lim",
  title =        "Investment and Risk Management with Online News and
                 Heterogeneous Networks",
  journal =      j-TWEB,
  volume =       "17",
  number =       "2",
  pages =        "8:1--8:??",
  month =        may,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3532858",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 17 18:10:45 MDT 2023",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3532858",
  abstract =     "Stock price movements in financial markets are
                 influenced by large volumes of news from diverse
                 sources on the web, e.g., online news outlets, blogs,
                 social media. Extracting useful information from online
                 news for financial tasks, e.g., forecasting stock
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "8",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Bouadjenek:2023:UCA,
  author =       "Mohamed Reda Bouadjenek and Scott Sanner and Ga Wu",
  title =        "A User-Centric Analysis of Social Media for Stock
                 Market Prediction",
  journal =      j-TWEB,
  volume =       "17",
  number =       "2",
  pages =        "9:1--9:??",
  month =        may,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3532856",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 17 18:10:45 MDT 2023",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3532856",
  abstract =     "Social media platforms such as Twitter or StockTwits
                 are widely used for sharing stock market opinions
                 between investors, traders, and entrepreneurs.
                 Empirically, previous work has shown that the content
                 posted on these social media platforms can be
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "9",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Kitzler:2023:DDF,
  author =       "Stefan Kitzler and Friedhelm Victor and Pietro Saggese
                 and Bernhard Haslhofer",
  title =        "Disentangling Decentralized Finance {(DeFi)}
                 Compositions",
  journal =      j-TWEB,
  volume =       "17",
  number =       "2",
  pages =        "10:1--10:??",
  month =        may,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3532857",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 17 18:10:45 MDT 2023",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3532857",
  abstract =     "We present a measurement study on compositions of
                 Decentralized Finance (DeFi) protocols, which aim to
                 disrupt traditional finance and offer services on top
                 of distributed ledgers, such as Ethereum. Understanding
                 DeFi compositions is of great importance, \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "10",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Piccardi:2023:LSC,
  author =       "Tiziano Piccardi and Martin Gerlach and Akhil Arora
                 and Robert West",
  title =        "A Large-Scale Characterization of How Readers Browse
                 {Wikipedia}",
  journal =      j-TWEB,
  volume =       "17",
  number =       "2",
  pages =        "11:1--11:??",
  month =        may,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3580318",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 17 18:10:45 MDT 2023",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3580318",
  abstract =     "Despite the importance and pervasiveness of Wikipedia
                 as one of the largest platforms for open knowledge,
                 surprisingly little is known about how people navigate
                 its content when seeking information. To bridge this
                 gap, we present the first systematic \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "11",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Sun:2023:ICW,
  author =       "Chang-Ai Sun and An Fu and Jingting Jia and Meng Li
                 and Jun Han",
  title =        "Improving Conformance of {Web} Services: a
                 Constraint-based Model-driven Approach",
  journal =      j-TWEB,
  volume =       "17",
  number =       "2",
  pages =        "12:1--12:??",
  month =        may,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3580515",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 17 18:10:45 MDT 2023",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3580515",
  abstract =     "Web services have been widely used to develop complex
                 distributed software systems in the context of Service
                 Oriented Architecture (SOA). As a standard for
                 describing Web services, the Web Service Description
                 Language (WSDL) provides a universal mechanism
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "12",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Jain:2023:OLI,
  author =       "Lokesh Jain and Rahul Katarya and Shelly Sachdeva",
  title =        "Opinion Leaders for Information Diffusion Using Graph
                 Neural Network in Online Social Networks",
  journal =      j-TWEB,
  volume =       "17",
  number =       "2",
  pages =        "13:1--13:??",
  month =        may,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3580516",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Mon Apr 17 18:10:45 MDT 2023",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3580516",
  abstract =     "Various opportunities are available to depict
                 different domains due to the diverse nature of social
                 networks and researchers' insatiable. An opinion leader
                 is a human entity or cluster of people who can redirect
                 human assessment strategy by intellectual \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "13",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Peng:2023:ISI,
  author =       "Hao Peng and Jian Yang and Jia Wu and Philip S. Yu",
  title =        "Introduction to the Special Issue on Advanced Graph
                 Mining on the {Web}: Theory, Algorithms, and
                 Applications: {Part 1}",
  journal =      j-TWEB,
  volume =       "17",
  number =       "3",
  pages =        "14:1--14:??",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3579360",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat Aug 19 07:32:23 MDT 2023",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3579360",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "14",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Yang:2023:RAS,
  author =       "Yingguang Yang and Renyu Yang and Yangyang Li and Kai
                 Cui and Zhiqin Yang and Yue Wang and Jie Xu and Haiyong
                 Xie",
  title =        "{RoSGAS}: Adaptive Social Bot Detection with
                 Reinforced Self-supervised {GNN} Architecture Search",
  journal =      j-TWEB,
  volume =       "17",
  number =       "3",
  pages =        "15:1--15:??",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3572403",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat Aug 19 07:32:23 MDT 2023",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3572403",
  abstract =     "Social bots are referred to as the automated accounts
                 on social networks that make attempts to behave like
                 humans. While Graph Neural Networks (GNNs) have been
                 massively applied to the field of social bot detection,
                 a huge amount of domain expertise and \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "15",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Du:2023:NRT,
  author =       "Haohua Du and Yue Wang and Xiaoya Xu and Mingsheng
                 Liu",
  title =        "{Niffler}: Real-time Device-level Anomalies Detection
                 in Smart Home",
  journal =      j-TWEB,
  volume =       "17",
  number =       "3",
  pages =        "16:1--16:??",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3586073",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat Aug 19 07:32:23 MDT 2023",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3586073",
  abstract =     "Device-level security has become a major concern in
                 smart home systems. Detecting problems in smart home
                 systems strives to increase accuracy in near real time
                 without hampering the regular tasks of the smart home.
                 The current state of the art in detecting \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "16",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Sun:2023:GDR,
  author =       "Li Sun and Yang Du and Shuai Gao and Junda Ye and
                 Feiyang Wang and Fuxin Ren and Mingchen Liang and Yue
                 Wang and Shuhai Wang",
  title =        "{GroupAligner}: a Deep Reinforcement Learning with
                 Domain Adaptation for Social Group Alignment",
  journal =      j-TWEB,
  volume =       "17",
  number =       "3",
  pages =        "17:1--17:??",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3580509",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat Aug 19 07:32:23 MDT 2023",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3580509",
  abstract =     "Social network alignment, which aims to uncover the
                 correspondence across different social networks, shows
                 fundamental importance in a wide spectrum of
                 applications such as cross-domain recommendation and
                 information propagation. In the literature, the
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "17",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Zhu:2023:MTG,
  author =       "Guixiang Zhu and Jie Cao and Lei Chen and Youquan Wang
                 and Zhan Bu and Shuxin Yang and Jianqing Wu and Zhiping
                 Wang",
  title =        "A Multi-Task Graph Neural Network with Variational
                 Graph Auto-Encoders for Session-Based Travel Packages
                 Recommendation",
  journal =      j-TWEB,
  volume =       "17",
  number =       "3",
  pages =        "18:1--18:??",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3577032",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat Aug 19 07:32:23 MDT 2023",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3577032",
  abstract =     "Session-based travel packages recommendation aims to
                 predict users' next click based on their current and
                 historical sessions recorded by Online Travel Agencies
                 (OTAs). Recently, an increasing number of studies
                 attempted to apply Graph Neural Networks (. \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "18",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Ahmed:2023:GAN,
  author =       "Usman Ahmed and Jerry Chun-Wei Lin and Gautam
                 Srivastava",
  title =        "Graph Attention Network for Text Classification and
                 Detection of Mental Disorder",
  journal =      j-TWEB,
  volume =       "17",
  number =       "3",
  pages =        "19:1--19:??",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3572406",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat Aug 19 07:32:23 MDT 2023",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3572406",
  abstract =     "A serious issue in today's society is Depression,
                 which can have a devastating impact on a person's
                 ability to cope in daily life. Numerous studies have
                 examined the use of data generated directly from users
                 using social media to diagnose and detect \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "19",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Li:2023:TIU,
  author =       "Qian Li and Jianxin Li and Lihong Wang and Cheng Ji
                 and Yiming Hei and Jiawei Sheng and Qingyun Sun and
                 Shan Xue and Pengtao Xie",
  title =        "Type Information Utilized Event Detection via
                 Multi-Channel {GNNs} in Electrical Power Systems",
  journal =      j-TWEB,
  volume =       "17",
  number =       "3",
  pages =        "20:1--20:??",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3577031",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat Aug 19 07:32:23 MDT 2023",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3577031",
  abstract =     "Event detection in power systems aims to identify
                 triggers and event types, which helps relevant
                 personnel respond to emergencies promptly and
                 facilitates the optimization of power supply
                 strategies. However, the limited length of short
                 electrical record \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "20",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Wang:2023:HGT,
  author =       "Shuhai Wang and Xin Liu and Xiao Pan and Hanjie Xu and
                 Mingrui Liu",
  title =        "Heterogeneous Graph Transformer for Meta-structure
                 Learning with Application in Text Classification",
  journal =      j-TWEB,
  volume =       "17",
  number =       "3",
  pages =        "21:1--21:??",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3580508",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat Aug 19 07:32:23 MDT 2023",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3580508",
  abstract =     "The prevalent heterogeneous Graph Neural Network (GNN)
                 models learn node and graph representations using
                 pre-defined meta-paths or only automatically
                 discovering meta-paths. However, the existing methods
                 suffer from information loss due to neglecting
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "21",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Gong:2023:RMC,
  author =       "Jibing Gong and Yao Wan and Ye Liu and Xuewen Li and
                 Yi Zhao and Cheng Wang and Yuting Lin and Xiaohan Fang
                 and Wenzheng Feng and Jingyi Zhang and Jie Tang",
  title =        "Reinforced {MOOCs} Concept Recommendation in
                 Heterogeneous Information Networks",
  journal =      j-TWEB,
  volume =       "17",
  number =       "3",
  pages =        "22:1--22:??",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3580510",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat Aug 19 07:32:23 MDT 2023",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3580510",
  abstract =     "Massive open online courses (MOOCs), which offer open
                 access and widespread interactive participation through
                 the internet, are quickly becoming the preferred method
                 for online and remote learning. Several MOOC platforms
                 offer the service of course \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "22",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Shang:2023:CST,
  author =       "Zhihua Shang and Hongtao Xie and Lingyun Yu and
                 Zhengjun Zha and Yongdong Zhang",
  title =        "Constructing Spatio-Temporal Graphs for Face Forgery
                 Detection",
  journal =      j-TWEB,
  volume =       "17",
  number =       "3",
  pages =        "23:1--23:??",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3580512",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat Aug 19 07:32:23 MDT 2023",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3580512",
  abstract =     "Recently, advanced development of facial manipulation
                 techniques threatens web information security, thus,
                 face forgery detection attracts a lot of attention. It
                 is clear that both spatial and temporal information of
                 facial videos contains the crucial \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "23",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}

@Article{Sheshbolouki:2023:SES,
  author =       "Aida Sheshbolouki and M. Tamer {\"O}zsu",
  title =        "{sGrow}: Explaining the Scale-Invariant Strength
                 Assortativity of Streaming Butterflies",
  journal =      j-TWEB,
  volume =       "17",
  number =       "3",
  pages =        "24:1--24:??",
  month =        aug,
  year =         "2023",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/3572408",
  ISSN =         "1559-1131 (print), 1559-114X (electronic)",
  ISSN-L =       "1559-1131",
  bibdate =      "Sat Aug 19 07:32:23 MDT 2023",
  bibsource =    "http://www.math.utah.edu/pub/tex/bib/tweb.bib",
  URL =          "https://dl.acm.org/doi/10.1145/3572408",
  abstract =     "Bipartite graphs are rich data structures with
                 prevalent applications and characteristic structural
                 features. However, less is known about their growth
                 patterns, particularly in streaming settings. Current
                 works study the patterns of static or aggregated
                 \ldots{}",
  acknowledgement = ack-nhfb,
  ajournal =     "ACM Trans. Web",
  articleno =    "24",
  fjournal =     "ACM Transactions on the Web (TWEB)",
  journal-URL =  "https://dl.acm.org/loi/tweb",
}