@Preamble{"\input bibnames.sty" #
"\ifx \undefined \booktitle \def \booktitle #1{{{\em #1}}} \fi" #
"\ifx \undefined \TM \def \TM {${}^{\sc TM}$} \fi"
}
@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/|"}
@String{j-TDS = "ACM Transactions on Data Science
(TDS)"}
@Article{Ooi:2020:IIE,
author = "Beng Chin Ooi",
title = "Inaugural Issue Editorial",
journal = j-TDS,
volume = "1",
number = "1",
pages = "1:1--1:2",
month = mar,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3368254",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Tue Apr 7 15:14:47 MDT 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/abs/10.1145/3368254",
acknowledgement = ack-nhfb,
articleno = "1",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Chakraborty:2020:EDA,
author = "Tanmoy Chakraborty and Noseong Park and Ayush Agarwal
and V. S. Subrahmanian",
title = "Ensemble Detection and Analysis of Communities in
Complex Networks",
journal = j-TDS,
volume = "1",
number = "1",
pages = "2:1--2:34",
month = mar,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3313374",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Tue Apr 7 15:14:47 MDT 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/abs/10.1145/3313374",
abstract = "Though much work has been done on ensemble clustering
in data mining, the application of ensemble methods to
community detection in networks is in its infancy. In
this article, we propose MeDOF, an ensemble method
which performs disjoint, overlapping, \ldots{}",
acknowledgement = ack-nhfb,
articleno = "2",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Li:2020:GBR,
author = "Guohui Li and Qi Chen and Bolong Zheng and Hongzhi Yin
and Quoc Viet Hung Nguyen and Xiaofang Zhou",
title = "Group-Based Recurrent Neural Networks for {POI}
Recommendation",
journal = j-TDS,
volume = "1",
number = "1",
pages = "3:1--3:18",
month = mar,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3343037",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Tue Apr 7 15:14:47 MDT 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/abs/10.1145/3343037",
abstract = "With the development of mobile Internet, many
location-based services have accumulated a large amount
of data that can be used for point-of-interest (POI)
recommendation. However, there are still challenges in
developing an unified framework to \ldots{}",
acknowledgement = ack-nhfb,
articleno = "3",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Li:2020:MAF,
author = "Xiangyang Li and Luis Herranz and Shuqiang Jiang",
title = "Multifaceted Analysis of Fine-Tuning in a Deep Model
for Visual Recognition",
journal = j-TDS,
volume = "1",
number = "1",
pages = "4:1--4:22",
month = mar,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3319500",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Tue Apr 7 15:14:47 MDT 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/abs/10.1145/3319500",
abstract = "In recent years, convolutional neural networks (CNNs)
have achieved impressive performance for various visual
recognition scenarios. CNNs trained on large labeled
datasets not only obtain significant performance on
most challenging benchmarks but also \ldots{}",
acknowledgement = ack-nhfb,
articleno = "4",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Ward:2020:PAA,
author = "Katrina Ward and Dan Lin and Sanjay Madria",
title = "A Parallel Algorithm For Anonymizing Large-scale
Trajectory Data",
journal = j-TDS,
volume = "1",
number = "1",
pages = "5:1--5:26",
month = mar,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3368639",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Tue Apr 7 15:14:47 MDT 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/abs/10.1145/3368639",
abstract = "With the proliferation of location-based services
enabled by a large number of mobile devices and
applications, the quantity of location data, such as
trajectories collected by service providers, is
gigantic. If these datasets could be published, then
\ldots{}",
acknowledgement = ack-nhfb,
articleno = "5",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Theil:2020:EFU,
author = "Christoph Kilian Theil and Sanja Stajner and Heiner
Stuckenschmidt",
title = "Explaining Financial Uncertainty through Specialized
Word Embeddings",
journal = j-TDS,
volume = "1",
number = "1",
pages = "6:1--6:19",
month = mar,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3343039",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Tue Apr 7 15:14:47 MDT 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/abs/10.1145/3343039",
abstract = "The detection of vague, speculative, or otherwise
uncertain language has been performed in the
encyclopedic, political, and scientific domains yet
left relatively untouched in finance. However, the
latter benefits from public sources of big financial
\ldots{}",
acknowledgement = ack-nhfb,
articleno = "6",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Beigi:2020:SPS,
author = "Ghazaleh Beigi and Huan Liu",
title = "A Survey on Privacy in Social Media: Identification,
Mitigation, and Applications",
journal = j-TDS,
volume = "1",
number = "1",
pages = "7:1--7:38",
month = mar,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3343038",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Tue Apr 7 15:14:47 MDT 2020",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/abs/10.1145/3343038",
abstract = "The increasing popularity of social media has
attracted a huge number of people to participate in
numerous activities on a daily basis. This results in
tremendous amounts of rich user-generated data. These
data provide opportunities for researchers and
\ldots{}",
acknowledgement = ack-nhfb,
articleno = "7",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Gan:2020:UMA,
author = "Wensheng Gan and Jerry Chun-Wei Lin and Jiexiong Zhang
and Philip S. Yu",
title = "Utility Mining across Multi-Sequences with
Individualized Thresholds",
journal = j-TDS,
volume = "1",
number = "2",
pages = "8:1--8:29",
month = jul,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3362070",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:05 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3362070",
abstract = "Utility-oriented pattern mining is an emerging topic,
since it can reveal high-utility patterns from
different types of data, which provides more
information than the traditional
frequency/confidence-based pattern mining models. The
utilities of various \ldots{}",
acknowledgement = ack-nhfb,
articleno = "8",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Yu:2020:MBI,
author = "Lei Yu and Guohui Li and Ling Yuan",
title = "Maximizing Boosted Influence Spread with Edge Addition
in Online Social Networks",
journal = j-TDS,
volume = "1",
number = "2",
pages = "9:1--9:21",
month = jul,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3364993",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:05 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3364993",
abstract = "Influence maximization with application to viral
marketing is a well-studied problem of finding a small
number of influential users in a social network to
maximize the spread of influence under certain
influence cascade models. However, almost all
\ldots{}",
acknowledgement = ack-nhfb,
articleno = "9",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Chowdhury:2020:RTP,
author = "Ranak Roy Chowdhury and Muhammad Abdullah Adnan and
Rajesh K. Gupta",
title = "Real-Time Principal Component Analysis",
journal = j-TDS,
volume = "1",
number = "2",
pages = "10:1--10:36",
month = jul,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3374750",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:05 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3374750",
abstract = "We propose a variant of Principal Component Analysis
(PCA) that is suited for real-time applications. In the
real-time version of the PCA problem, we maintain a
window over the most recent data and project every
incoming row of data into a lower-. \ldots{}",
acknowledgement = ack-nhfb,
articleno = "10",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Wu:2020:DST,
author = "Gene P. K. Wu and Keith C. C. Chan",
title = "Discovery of Spatio-Temporal Patterns in Multivariate
Spatial Time Series",
journal = j-TDS,
volume = "1",
number = "2",
pages = "11:1--11:22",
month = jul,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3374748",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:05 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3374748",
abstract = "With the advancement of the computing technology and
its wide range of applications, collecting large sets
of multivariate time series in multiple geographical
locations introduces a problem of identifying
interesting spatio-temporal patterns. We \ldots{}",
acknowledgement = ack-nhfb,
articleno = "11",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Bessa:2020:EDM,
author = "Aline Bessa and Juliana Freire and Tamraparni Dasu and
Divesh Srivastava",
title = "Effective Discovery of Meaningful Outlier
Relationships",
journal = j-TDS,
volume = "1",
number = "2",
pages = "12:1--12:33",
month = jul,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3385192",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:05 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3385192",
abstract = "We propose Predictable Outliers in Data-trendS (PODS),
a method that, given a collection of temporal datasets,
derives data-driven explanations for outliers by
identifying meaningful relationships between them.
First, we formalize the notion of \ldots{}",
acknowledgement = ack-nhfb,
articleno = "12",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Nashaat:2020:AGL,
author = "Mona Nashaat and Aindrila Ghosh and James Miller and
Shaikh Quader",
title = "{Asterisk}: Generating Large Training Datasets with
Automatic Active Supervision",
journal = j-TDS,
volume = "1",
number = "2",
pages = "13:1--13:25",
month = jul,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3385188",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:05 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3385188",
abstract = "Labeling datasets is one of the most expensive
bottlenecks in data preprocessing tasks in machine
learning. Therefore, organizations, in many domains,
are applying weak supervision to produce noisy labels.
However, since weak supervision relies on \ldots{}",
acknowledgement = ack-nhfb,
articleno = "13",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Li:2020:ISI,
author = "Yanhua Li and Jie Bao and Zhi-Li Zhang and Saif
Benjaafar",
title = "Introduction to the Special Issue on Urban Computing
and Smart Cities",
journal = j-TDS,
volume = "1",
number = "3",
pages = "14:1--14:2",
month = oct,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3412392",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:05 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3412392",
acknowledgement = ack-nhfb,
articleno = "14",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Sainju:2020:MRS,
author = "Arpan Man Sainju and Zhe Jiang",
title = "Mapping Road Safety Features from Streetview Imagery:
a Deep Learning Approach",
journal = j-TDS,
volume = "1",
number = "3",
pages = "15:1--15:20",
month = oct,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3362069",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:05 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3362069",
abstract = "Each year, an average of around 6 million car
accidents occur in the United States. Road safety
features (e.g., concrete barriers, metal crash
barriers, rumble strips) play an important role in
preventing or mitigating vehicle crashes. Accurate maps
of \ldots{}",
acknowledgement = ack-nhfb,
articleno = "15",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Tian:2020:UEB,
author = "Zhihong Tian and Chaochao Luo and Hui Lu and Shen Su
and Yanbin Sun and Man Zhang",
title = "User and Entity Behavior Analysis under Urban Big
Data",
journal = j-TDS,
volume = "1",
number = "3",
pages = "16:1--16:19",
month = oct,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3374749",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:05 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3374749",
abstract = "Recently, the urban network infrastructure has
undergone a rapid expansion that is increasingly
generating a large quantity of data and transforming
our cities into smart cities. However, serious security
problems arise with this development with more
\ldots{}",
acknowledgement = ack-nhfb,
articleno = "16",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Xie:2020:UFR,
author = "Yiqun Xie and Shashi Shekhar",
title = "A Unified Framework for Robust and Efficient Hotspot
Detection in Smart Cities",
journal = j-TDS,
volume = "1",
number = "3",
pages = "17:1--17:29",
month = oct,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3379562",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:05 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3379562",
abstract = "Given N geo-located point instances (e.g., crime or
disease cases) in a spatial domain, we aim to detect
sub-regions (i.e., hotspots) that have a higher
probability density of generating such instances than
the others. Hotspot detection has been widely
\ldots{}",
acknowledgement = ack-nhfb,
articleno = "17",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Ding:2020:TAH,
author = "Weilong Ding and Zhuofeng Zhao and Jianwu Wang and Han
Li",
title = "Task Allocation in Hybrid Big Data Analytics for Urban
{IoT} Applications",
journal = j-TDS,
volume = "1",
number = "3",
pages = "18:1--18:22",
month = oct,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3374751",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:05 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3374751",
abstract = "In urban Internet of Things (IoT) environments, data
generated in real time could be processed by analytical
applications in online or offline mode. In the
management perspective of runtime environments, such
modes can hardly be supported in a unified \ldots{}",
acknowledgement = ack-nhfb,
articleno = "18",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Yang:2020:SAT,
author = "Zhong Yang and Bolong Zheng and Guohui Li and Nguyen
Quoc Viet Hung and Guanfeng Liu and Kai Zheng",
title = "Searching Activity Trajectories by Exemplar",
journal = j-TDS,
volume = "1",
number = "3",
pages = "19:1--19:18",
month = oct,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3379561",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:05 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3379561",
abstract = "The rapid explosion of urban cities has modernized the
residents' lives and generated a large amount of data
(e.g., human mobility data, traffic data, and
geographical data), especially the activity trajectory
data that contains spatial and temporal as \ldots{}",
acknowledgement = ack-nhfb,
articleno = "19",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Xu:2020:AWF,
author = "Xin Xu and Yanjie Fu and Jingyi Wu and Yuqi Wang and
Zeyu Huang and Zhiguo Fu and Minghao Yin",
title = "Adaptive Weighted Finite Mixture Model: Identifying
the Feature-Influence of Real Estate",
journal = j-TDS,
volume = "1",
number = "3",
pages = "20:1--20:16",
month = oct,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3379560",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:05 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3379560",
abstract = "It is significant for real estate investors to
understand how the construction environments and
building characteristics impact the housing unit price.
However, it is challenging for identifying the complex
feature-influence from construction \ldots{}",
acknowledgement = ack-nhfb,
articleno = "20",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Zeidan:2020:GEL,
author = "Ayman Zeidan and Eemil Lagerspetz and Kai Zhao and
Petteri Nurmi and Sasu Tarkoma and Huy T. Vo",
title = "{GeoMatch}: Efficient Large-scale Map Matching on
{Apache Spark}",
journal = j-TDS,
volume = "1",
number = "3",
pages = "21:1--21:30",
month = oct,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3402904",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:05 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3402904",
abstract = "We develop GeoMatch as a novel, scalable, and
efficient big-data pipeline for large-scale map
matching on Apache Spark. GeoMatch improves existing
spatial big-data solutions by utilizing a novel spatial
partitioning scheme inspired by Hilbert space-.
\ldots{}",
acknowledgement = ack-nhfb,
articleno = "21",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Li:2020:PGE,
author = "Yan Li and Pratik Kotwal and Pengyue Wang and Yiqun
Xie and Shashi Shekhar and William Northrop",
title = "Physics-guided Energy-efficient Path Selection Using
On-board Diagnostics Data",
journal = j-TDS,
volume = "1",
number = "3",
pages = "22:1--22:28",
month = oct,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3406596",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:05 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3406596",
abstract = "Given a spatial graph, an origin and a destination,
and on-board diagnostics (OBD) data, the
energy-efficient path selection problem aims to find
the path with the least expected energy consumption
(EEC). Two main objectives of smart cities are
\ldots{}",
acknowledgement = ack-nhfb,
articleno = "22",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Arabghalizi:2020:DDB,
author = "Tahereh Arabghalizi and Alexandros Labrinidis",
title = "Data-driven Bus Crowding Prediction Models Using
Context-specific Features",
journal = j-TDS,
volume = "1",
number = "3",
pages = "23:1--23:33",
month = oct,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3406962",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:05 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3406962",
abstract = "Public transit is one of the first things that come to
mind when someone talks about ``smart cities.'' As a
result, many technologies, applications, and
infrastructure have already been deployed to bring the
promise of the smart city to public \ldots{}",
acknowledgement = ack-nhfb,
articleno = "23",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Hu:2020:ISI,
author = "Haibo Hu and Rik Sarkar and Zhengzhang Chen",
title = "Introduction to the Special Issue on Retrieving and
Learning from {Internet of Things} Data",
journal = j-TDS,
volume = "1",
number = "4",
pages = "24:1--24:1",
month = dec,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3426368",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:06 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3426368",
acknowledgement = ack-nhfb,
articleno = "24",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Fang:2020:HHR,
author = "Liming Fang and Hongwei Zhu and Boqing Lv and Zhe Liu
and Weizhi Meng and Yu Yu and Shouling Ji and Zehong
Cao",
title = "{HandiText}: Handwriting Recognition Based on Dynamic
Characteristics with Incremental {LSTM}",
journal = j-TDS,
volume = "1",
number = "4",
pages = "25:1--25:18",
month = dec,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3385189",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:06 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/cryptography2020.bib;
http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3385189",
abstract = "The Internet of Things (IoT) is a new manifestation of
data science. To ensure the credibility of data about
IoT devices, authentication has gradually become an
important research topic in the IoT ecosystem. However,
traditional graphical passwords and text passwords can
cause user's serious memory burdens. Therefore, a
convenient method for determining user identity is
needed. In this article, we propose a handwriting
recognition authentication scheme named HandiText based
on behavior and biometrics features. When people write
a word by hand, HandiText captures their static
biological features and dynamic behavior features
during the writing process (writing speed, pressure,
etc.). The features are related to habits, which make
it difficult for attackers to imitate. We also carry
out algorithms comparisons and experiments evaluation
to prove the reliability of our scheme. The experiment
results show that the Long Short-Term Memory has the
best classification accuracy, reaching 99\% while
keeping relatively low false-positive rate and
false-negative rate. We also test other datasets, the
average accuracy of HandiText reach 98\%, with strong
generalization ability. Besides, the 324 users we
investigated indicated that they are willing to use
this scheme on IoT devices.",
acknowledgement = ack-nhfb,
articleno = "25",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Li:2020:TTR,
author = "Huan Li and Hua Lu and Gang Chen and Ke Chen and
Qinkuang Chen and Lidan Shou",
title = "Toward Translating Raw Indoor Positioning Data into
Mobility Semantics",
journal = j-TDS,
volume = "1",
number = "4",
pages = "26:1--26:37",
month = dec,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3385190",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:06 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3385190",
abstract = "Indoor mobility analyses are increasingly interesting
due to the rapid growth of raw indoor positioning data
obtained from IoT infrastructure. However, high-level
analyses are still in urgent need of a concise but
semantics-oriented representation of \ldots{}",
acknowledgement = ack-nhfb,
articleno = "26",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Busany:2020:IBQ,
author = "Nimrod Busany and Han {Van Der Aa} and Arik
Senderovich and Avigdor Gal and Matthias Weidlich",
title = "Interval-based Queries over Lossy {IoT} Event
Streams",
journal = j-TDS,
volume = "1",
number = "4",
pages = "27:1--27:27",
month = dec,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3385191",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:06 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3385191",
abstract = "Recognising patterns that correlate multiple events
over time becomes increasingly important in
applications that exploit the Internet of Things,
reaching from urban transportation through surveillance
monitoring to business workflows. In many real-.
\ldots{}",
acknowledgement = ack-nhfb,
articleno = "27",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Schmeisser:2020:CCS,
author = "Stephan Schmei{\ss}er and Gregor Schiele",
title = "{coSense}: The Collaborative Sensing Middleware for
the {Internet}-of-Things",
journal = j-TDS,
volume = "1",
number = "4",
pages = "28:1--28:21",
month = dec,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3395233",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:06 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3395233",
abstract = "We present coSense -the collaborative, fault-tolerant,
and adaptive sensing middleware for the
Internet-of-Things (IoT). By actively harnessing the
greatest asset of the IoT, the sheer number of devices,
coSense is able to provide easy data acquisition
\ldots{}",
acknowledgement = ack-nhfb,
articleno = "28",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Elbassuoni:2020:FSO,
author = "Shady Elbassuoni and Sihem Amer-Yahia and Ahmad
Ghizzawi",
title = "Fairness of Scoring in Online Job Marketplaces",
journal = j-TDS,
volume = "1",
number = "4",
pages = "29:1--29:30",
month = dec,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3402883",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:06 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3402883",
abstract = "We study fairness of scoring in online job
marketplaces. We focus on group fairness and aim to
algorithmically explore how a scoring function, through
which individuals are ranked for jobs, treats different
demographic groups. Previous work on group-. \ldots{}",
acknowledgement = ack-nhfb,
articleno = "29",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Yang:2020:MFR,
author = "Luoying Yang and Zhou Xu and Jiebo Luo",
title = "Measuring Female Representation and Impact in Films
over Time",
journal = j-TDS,
volume = "1",
number = "4",
pages = "30:1--30:14",
month = dec,
year = "2020",
CODEN = "????",
DOI = "https://doi.org/10.1145/3411213",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:06 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3411213",
abstract = "Women have always been underrepresented in movies and
not until recently has the representation of women in
movies improved. To investigate the improvement of
female representation and its relationship with a
movie's success, we propose a new measure, \ldots{}",
acknowledgement = ack-nhfb,
articleno = "30",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Shi:2021:NAT,
author = "Tian Shi and Yaser Keneshloo and Naren Ramakrishnan
and Chandan K. Reddy",
title = "Neural Abstractive Text Summarization with
Sequence-to-Sequence Models",
journal = j-TDS,
volume = "2",
number = "1",
pages = "1:1--1:37",
month = jan,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3419106",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:07 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3419106",
abstract = "In the past few years, neural abstractive text
summarization with sequence-to-sequence (seq2seq)
models have gained a lot of popularity. Many
interesting techniques have been proposed to improve
seq2seq models, making them capable of handling
different \ldots{}",
acknowledgement = ack-nhfb,
articleno = "1",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Li:2021:ISI,
author = "Yanhua Li and Jie Bao and Zhi-Li Zhang and Saif
Benjaafar",
title = "Introduction to the Special Issue on Urban Computing
and Smart Cities",
journal = j-TDS,
volume = "2",
number = "1",
pages = "2e:1--2e:2",
month = jan,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3441679",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:07 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3441679",
acknowledgement = ack-nhfb,
articleno = "2e",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Liu:2021:SBU,
author = "Xiuming Liu and Edith Ngai and Dave Zachariah",
title = "Scalable Belief Updating for Urban Air Quality
Modeling and Prediction",
journal = j-TDS,
volume = "2",
number = "1",
pages = "2:1--2:19",
month = jan,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3402903",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:07 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3402903",
abstract = "Air pollution is one of the major concerns in global
urbanization. Data science can help to understand the
dynamics of air pollution and build reliable
statistical models to forecast air pollution levels. To
achieve these goals, one needs to learn the \ldots{}",
acknowledgement = ack-nhfb,
articleno = "2",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Iyengar:2021:WDD,
author = "Srinivasan Iyengar and Stephen Lee and David Irwin and
Prashant Shenoy and Benjamin Weil",
title = "{WattScale}: a Data-driven Approach for Energy
Efficiency Analytics of Buildings at Scale",
journal = j-TDS,
volume = "2",
number = "1",
pages = "3:1--3:25",
month = jan,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3406961",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:07 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3406961",
abstract = "Buildings consume over 40\% of the total energy in
modern societies, and improving their energy efficiency
can significantly reduce our energy footprint. In this
article, we present WattScale, a data-driven approach
to identify the least energy-efficient \ldots{}",
acknowledgement = ack-nhfb,
articleno = "3",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Jiang:2021:TUH,
author = "Renhe Jiang and Xuan Song and Zipei Fan and Tianqi Xia
and Zhaonan Wang and Quanjun Chen and Zekun Cai and
Ryosuke Shibasaki",
title = "Transfer Urban Human Mobility via {POI} Embedding over
Multiple Cities",
journal = j-TDS,
volume = "2",
number = "1",
pages = "4:1--4:26",
month = jan,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3416914",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:07 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3416914",
abstract = "Rapidly developing location acquisition technologies
provide a powerful tool for understanding and
predicting human mobility in cities, which is very
significant for urban planning, traffic regulation, and
emergency management. However, with the \ldots{}",
acknowledgement = ack-nhfb,
articleno = "4",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Babicheva:2021:EVR,
author = "Tatiana Babicheva and Matej Cebecauer and Dominique
Barth and Wilco Burghout and Le{\"\i}la Kloul",
title = "Empty Vehicle Redistribution with Time Windows in
Autonomous Taxi Systems",
journal = j-TDS,
volume = "2",
number = "1",
pages = "5:1--5:22",
month = jan,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3416915",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:07 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3416915",
abstract = "In this article, we investigate empty vehicle
redistribution algorithms with time windows for
personal rapid transit or autonomous station-based taxi
services, from a passenger service perspective. We
present an Index Based Redistribution Time Limited
\ldots{}",
acknowledgement = ack-nhfb,
articleno = "5",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Molinaro:2021:SST,
author = "Cristian Molinaro and Chiara Pulice and Anja Subasic
and Abigail Bartolome and V. S. Subrahmanian",
title = "{STAR: Summarizing Timed Association Rules}",
journal = j-TDS,
volume = "2",
number = "1",
pages = "6:1--6:36",
month = jan,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3419107",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Wed Mar 10 06:28:07 MST 2021",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3419107",
abstract = "Timed association rules (TARs) generalize classical
association rules (ARs) so that we can express temporal
dependencies of the form ``If $X$ is true at time $t$,
then $Y$ will likely be true at time $ (t + \tau)$.''
As with ARs, solving the TAR mining problem can
\ldots{}",
acknowledgement = ack-nhfb,
articleno = "6",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Zoppi:2021:UAD,
author = "Tommaso Zoppi and Andrea Ceccarelli and Tommaso
Capecchi and Andrea Bondavalli",
title = "Unsupervised Anomaly Detectors to Detect Intrusions in
the Current Threat Landscape",
journal = j-TDS,
volume = "2",
number = "2",
pages = "7:1--7:26",
month = may,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3441140",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:14 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3441140",
abstract = "Anomaly detection aims at identifying unexpected
fluctuations in the expected behavior of a given
system. It is acknowledged as a reliable answer to the
identification of zero-day attacks to such extent,
several ML algorithms that suit for binary \ldots{}",
acknowledgement = ack-nhfb,
articleno = "7",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Cheng:2021:MTP,
author = "Lu Cheng and Ruocheng Guo and Yasin N. Silva and
Deborah Hall and Huan Liu",
title = "Modeling Temporal Patterns of Cyberbullying Detection
with Hierarchical Attention Networks",
journal = j-TDS,
volume = "2",
number = "2",
pages = "8:1--8:23",
month = may,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3441141",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:14 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3441141",
abstract = "Cyberbullying is rapidly becoming one of the most
serious online risks for adolescents. This has
motivated work on machine learning methods to automate
the process of cyberbullying detection, which have so
far mostly viewed cyberbullying as one-off \ldots{}",
acknowledgement = ack-nhfb,
articleno = "8",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Zhou:2021:ISI,
author = "Ke Zhou and Jingkuan Song",
title = "Introduction to the Special Issue on Learning-based
Support for Data Science Applications",
journal = j-TDS,
volume = "2",
number = "2",
pages = "9:1--9:1",
month = may,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3450751",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:14 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3450751",
acknowledgement = ack-nhfb,
articleno = "9",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Li:2021:TAN,
author = "Yamin Li and Jun Zhang and Zhongliang Yang and Ru
Zhang",
title = "Topic-aware Neural Linguistic Steganography Based on
Knowledge Graphs",
journal = j-TDS,
volume = "2",
number = "2",
pages = "10:1--10:13",
month = may,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3418598",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:14 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3418598",
abstract = "The core challenge of steganography is always how to
improve the hidden capacity and the concealment. Most
current generation-based linguistic steganography
methods only consider the probability distribution
between text characters, and the emotion and \ldots{}",
acknowledgement = ack-nhfb,
articleno = "10",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Liu:2021:DHB,
author = "Yu Liu and Yangtao Wang and Lianli Gao and Chan Guo
and Yanzhao Xie and Zhili Xiao",
title = "Deep Hash-based Relevance-aware Data Quality
Assessment for Image Dark Data",
journal = j-TDS,
volume = "2",
number = "2",
pages = "11:1--11:26",
month = may,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3420038",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:14 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3420038",
abstract = "Data mining can hardly solve but always faces a
problem that there is little meaningful information
within the dataset serving a given requirement. Faced
with multiple unknown datasets, to allocate data mining
resources to acquire more desired data, it is
\ldots{}",
acknowledgement = ack-nhfb,
articleno = "11",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Zhang:2021:SIR,
author = "Xinyu Zhang and Xiaocui Li and Xiao-Yuan Jing and Li
Cheng",
title = "Simultaneous Image Reconstruction and Feature Learning
with {$3$D-CNNs} for Image Set-Based Classification",
journal = j-TDS,
volume = "2",
number = "2",
pages = "12:1--12:13",
month = may,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3420037",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:14 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3420037",
abstract = "Image set-based classification has attracted
substantial research interest because of its broad
applications. Recently, lots of methods based on
feature learning or dictionary learning have been
developed to solve this problem, and some of them have
made \ldots{}",
acknowledgement = ack-nhfb,
articleno = "12",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Yang:2021:BRP,
author = "Ru Yang and Yuhui Deng and Yi Zhou and Ping Huang",
title = "Boosting the Restoring Performance of Deduplication
Data by Classifying Backup Metadata",
journal = j-TDS,
volume = "2",
number = "2",
pages = "13:1--13:16",
month = may,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3437261",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:14 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3437261",
abstract = "Restoring data is the main purpose of data backup in
storage systems. The fragmentation issue, caused by
physically scattering logically continuous data across
a variety of disk locations, poses a negative impact on
the restoring performance of a \ldots{}",
acknowledgement = ack-nhfb,
articleno = "13",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Zandavi:2021:MUR,
author = "Seid Miad Zandavi and Vera Chung and Ali Anaissi",
title = "Multi-user Remote Lab: Timetable Scheduling Using
Simplex Nondominated Sorting Genetic Algorithm",
journal = j-TDS,
volume = "2",
number = "2",
pages = "14:1--14:13",
month = may,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3437260",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:14 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3437260",
abstract = "The scheduling of multi-user remote laboratories is
modeled as a multimodal function for the proposed
optimization algorithm. The hybrid optimization
algorithm, hybridization of the Nelder--Mead Simplex
algorithm, and Non-dominated Sorting Genetic \ldots{}",
acknowledgement = ack-nhfb,
articleno = "14",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Gao:2021:MGD,
author = "Hongchao Gao and Yujia Li and Jiao Dai and Xi Wang and
Jizhong Han and Ruixuan Li",
title = "Multi-granularity Deep Local Representations for
Irregular Scene Text Recognition",
journal = j-TDS,
volume = "2",
number = "2",
pages = "15:1--15:18",
month = may,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3446971",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:14 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3446971",
abstract = "Recognizing irregular text from natural scene images
is challenging due to the unconstrained appearance of
text, such as curvature, orientation, and distortion.
Recent recognition networks regard this task as a text
sequence labeling problem and most \ldots{}",
acknowledgement = ack-nhfb,
articleno = "15",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Tian:2021:TST,
author = "Xiancai Tian and Baihua Zheng and Yazhe Wang and
Hsiao-Ting Huang and Chih-Chieh Hung",
title = "{TRIPDECODER}: Study Travel Time Attributes and Route
Preferences of Metro Systems from Smart Card Data",
journal = j-TDS,
volume = "2",
number = "3",
pages = "16:1--16:21",
month = aug,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3430768",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:15 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3430768",
abstract = "In this article, we target at recovering the exact
routes taken by commuters inside a metro system that
are not captured by an Automated Fare Collection (AFC)
system and hence remain unknown. We strategically
propose two inference tasks to handle the \ldots{}",
acknowledgement = ack-nhfb,
articleno = "16",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Steadman:2021:KDS,
author = "Liam Steadman and Nathan Griffiths and Stephen Jarvis
and Mark Bell and Shaun Helman and Caroline Wallbank",
title = "{kD-STR}: a Method for Spatio-Temporal Data Reduction
and Modelling",
journal = j-TDS,
volume = "2",
number = "3",
pages = "17:1--17:31",
month = may,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3439334",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:15 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3439334",
abstract = "Analysing and learning from spatio-temporal datasets
is an important process in many domains, including
transportation, healthcare and meteorology. In
particular, data collected by sensors in the
environment allows us to understand and model the
processes \ldots{}",
acknowledgement = ack-nhfb,
articleno = "17",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Nashaat:2021:TUR,
author = "Mona Nashaat and Aindrila Ghosh and James Miller and
Shaikh Quader",
title = "{TabReformer}: Unsupervised Representation Learning
for Erroneous Data Detection",
journal = j-TDS,
volume = "2",
number = "3",
pages = "18:1--18:29",
month = may,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3447541",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:15 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3447541",
abstract = "Error detection is a crucial preliminary phase in any
data analytics pipeline. Existing error detection
techniques typically target specific types of errors.
Moreover, most of these detection models either require
user-defined rules or ample hand-labeled \ldots{}",
acknowledgement = ack-nhfb,
articleno = "18",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Behrens:2021:DCC,
author = "Hans Walter Behrens and K. Sel{\c{c}}uk Candan and
Xilun Chen and Yash Garg and Mao-Lin Li and Xinsheng Li
and Sicong Liu and Maria Luisa Sapino and Md Shadab and
Dalton Turner and Magesh Vijayakumaren",
title = "{DataStorm}: Coupled, Continuous Simulations for
Complex Urban Environments",
journal = j-TDS,
volume = "2",
number = "3",
pages = "19:1--19:37",
month = aug,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3447572",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:15 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3447572",
abstract = "Urban systems are characterized by complexity and
dynamicity. Data-driven simulations represent a
promising approach in understanding and predicting
complex dynamic processes in the presence of shifting
demands of urban systems. Yet, today's silo-based,
\ldots{}",
acknowledgement = ack-nhfb,
articleno = "19",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Jia:2021:PGM,
author = "Xiaowei Jia and Jared Willard and Anuj Karpatne and
Jordan S. Read and Jacob A. Zwart and Michael Steinbach
and Vipin Kumar",
title = "Physics-Guided Machine Learning for Scientific
Discovery: an Application in Simulating Lake
Temperature Profiles",
journal = j-TDS,
volume = "2",
number = "3",
pages = "20:1--20:26",
month = may,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3447814",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:15 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3447814",
abstract = "Physics-based models are often used to study
engineering and environmental systems. The ability to
model these systems is the key to achieving our future
environmental sustainability and improving the quality
of human life. This article focuses on \ldots{}",
acknowledgement = ack-nhfb,
articleno = "20",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Gramaglia:2021:GTP,
author = "Marco Gramaglia and Marco Fiore and Angelo Furno and
Razvan Stanica",
title = "{GLOVE}: Towards Privacy-Preserving Publishing of
Record-Level-Truthful Mobile Phone Trajectories",
journal = j-TDS,
volume = "2",
number = "3",
pages = "21:1--21:36",
month = aug,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3451178",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:15 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3451178",
abstract = "Datasets of mobile phone trajectories collected by
network operators offer an unprecedented opportunity to
discover new knowledge from the activity of large
populations of millions. However, publishing such
trajectories also raises significant privacy \ldots{}",
acknowledgement = ack-nhfb,
articleno = "21",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Chakraborty:2021:ATN,
author = "Vishal Chakraborty and Theo Delemazure and Benny
Kimelfeld and Phokion G. Kolaitis and Kunal Relia and
Julia Stoyanovich",
title = "Algorithmic Techniques for Necessary and Possible
Winners",
journal = j-TDS,
volume = "2",
number = "3",
pages = "22:1--22:23",
month = aug,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3458472",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:15 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3458472",
abstract = "We investigate the practical aspects of computing the
necessary and possible winners in elections over
incomplete voter preferences. In the case of the
necessary winners, we show how to implement and
accelerate the polynomial-time algorithm of Xia and
\ldots{}",
acknowledgement = ack-nhfb,
articleno = "22",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Song:2021:PPC,
author = "Jie Song and Qiang He and Feifei Chen and Ye Yuan and
Ge Yu",
title = "{PoBery}: Possibly-complete Big Data Queries with
Probabilistic Data Placement and Scanning",
journal = j-TDS,
volume = "2",
number = "3",
pages = "23:1--23:28",
month = aug,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3465375",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:15 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3465375",
abstract = "In big data query processing, there is a trade-off
between query accuracy and query efficiency, for
example, sampling query approaches trade-off query
completeness for efficiency. In this article, we argue
that query performance can be significantly \ldots{}",
acknowledgement = ack-nhfb,
articleno = "23",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Dey:2021:SRC,
author = "Paramita Dey and Subhayan Bhattacharya and Sarbani
Roy",
title = "A Survey on the Role of Centrality as Seed Nodes for
Information Propagation in Large Scale Network",
journal = j-TDS,
volume = "2",
number = "3",
pages = "24:1--24:25",
month = aug,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3465374",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:15 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3465374",
abstract = "From the popular concept of six-degree separation,
social networks are generally analyzed in the
perspective of small world networks where centrality of
nodes play a pivotal role in information propagation.
However, working with a large dataset of a scale-.
\ldots{}",
acknowledgement = ack-nhfb,
articleno = "24",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Leng:2021:TEA,
author = "Yan Leng and Alejandro Noriega and Alex Pentland",
title = "Tourism Event Analytics with Mobile Phone Data",
journal = j-TDS,
volume = "2",
number = "3",
pages = "25:1--25:22",
month = aug,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3479975",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:15 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3479975",
abstract = "Tourism has been an increasingly significant
contributor to the economy, society, and environment.
Policy-making and research on tourism traditionally
rely on surveys and economic datasets, which are based
on small samples and depict tourism dynamics at a
\ldots{}",
acknowledgement = ack-nhfb,
articleno = "25",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Maji:2021:CUF,
author = "Subhadip Maji and Smarajit Bose",
title = "{CBIR} Using Features Derived by Deep Learning",
journal = j-TDS,
volume = "2",
number = "3",
pages = "26:1--26:24",
month = aug,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3470568",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:15 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3470568",
abstract = "In a Content-based Image Retrieval (CBIR) System, the
task is to retrieve similar images from a large
database given a query image. The usual procedure is to
extract some useful features from the query image and
retrieve images that have a similar set of \ldots{}",
acknowledgement = ack-nhfb,
articleno = "26",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Du:2021:AED,
author = "Zhekai Du and Jingjing Li and Lei Zhu and Ke Lu and
Heng Tao Shen",
title = "Adversarial Energy Disaggregation",
journal = j-TDS,
volume = "2",
number = "4",
pages = "27:1--27:16",
month = nov,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3477301",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:16 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3477301",
abstract = "Energy disaggregation, also known as non-intrusive
load monitoring (NILM), challenges the problem of
separating the whole-home electricity usage into
appliance-specific individual consumptions, which is a
typical application of data analysis. NILM aims to
\ldots{}",
acknowledgement = ack-nhfb,
articleno = "27",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Desmet:2021:RDP,
author = "Chance Desmet and Diane J. Cook",
title = "Recent Developments in Privacy-preserving Mining of
Clinical Data",
journal = j-TDS,
volume = "2",
number = "4",
pages = "28:1--28:32",
month = nov,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3447774",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:16 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3447774",
abstract = "With the dramatic improvements in both the capability
to collect personal data and the capability to analyze
large amounts of data, increasingly sophisticated and
personal insights are being drawn. These insights are
valuable for clinical applications but \ldots{}",
acknowledgement = ack-nhfb,
articleno = "28",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Zhang:2021:HSS,
author = "Jiaru Zhang and Ruhui Ma and Tao Song and Yang Hua and
Zhengui Xue and Chenyang Guan and Haibing Guan",
title = "Hierarchical Satellite System Graph for Approximate
Nearest Neighbor Search on Big Data",
journal = j-TDS,
volume = "2",
number = "4",
pages = "32:1--32:15",
month = nov,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3488377",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:16 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3488377",
abstract = "Approximate nearest neighbor search is a classical
problem in data science, which is widely applied in
many fields. With the rapid growth of data in the real
world, it becomes more and more important to speed up
the nearest neighbor search process. \ldots{}",
acknowledgement = ack-nhfb,
articleno = "32",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Gao:2021:QTN,
author = "Yuan Gao and Laurence T. Yang and Dehua Zheng and Jing
Yang and Yaliang Zhao",
title = "Quantized Tensor Neural Network",
journal = j-TDS,
volume = "2",
number = "4",
pages = "33:1--33:18",
month = nov,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3491255",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:16 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3491255",
abstract = "Tensor network as an effective computing framework for
efficient processing and analysis of high-dimensional
data has been successfully applied in many fields.
However, the performance of traditional tensor networks
still cannot match the strong fitting \ldots{}",
acknowledgement = ack-nhfb,
articleno = "33",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Ding:2021:DPD,
author = "Xiaofeng Ding and Lin Chen and Pan Zhou and Wenbin
Jiang and Hai Jin",
title = "Differentially Private Deep Learning with Iterative
Gradient Descent Optimization",
journal = j-TDS,
volume = "2",
number = "4",
pages = "34:1--34:27",
month = nov,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3491254",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:16 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3491254",
abstract = "Deep learning has achieved great success in various
areas and its success is closely linked to the
availability of massive data. But in general, a large
dataset could include sensitive data and therefore the
model should have the capability to avoid \ldots{}",
acknowledgement = ack-nhfb,
articleno = "34",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Agarwal:2021:STS,
author = "Mridul Agarwal and Vaneet Aggarwal and Abhishek K.
Umrawal and Christopher J. Quinn",
title = "Stochastic Top {$K$}-Subset Bandits with Linear Space
and Non-Linear Feedback with Applications to Social
Influence Maximization",
journal = j-TDS,
volume = "2",
number = "4",
pages = "38:1--38:39",
month = nov,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3507787",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Thu Feb 17 07:13:16 MST 2022",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3507787",
abstract = "There are numerous real-world problems where a user
must make decisions under uncertainty. For the problem
of influence maximization on a social network, for
example, the user must select a set of K influencers
who will jointly have a large influence on \ldots{}",
acknowledgement = ack-nhfb,
articleno = "38",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Xia:2021:SBA,
author = "Feng Xia and Teng Guo and Xiaomei Bai and Adrian
Shatte and Zitao Liu and Jiliang Tang",
title = "{SUMMER}: Bias-aware Prediction of Graduate Employment
Based on Educational Big Data",
journal = j-TDS,
volume = "2",
number = "4",
pages = "39:1--39:??",
month = nov,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3510361",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Fri Aug 25 12:23:02 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3510361",
abstract = "The failure of obtaining employment could lead to
serious psychosocial outcomes such as depression and
substance abuse, especially for college students who
\ldots{}",
acknowledgement = ack-nhfb,
ajournal = "",
articleno = "39",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Goodman:2021:DBP,
author = "Joel Goodman and Sharham Sarkani and Thomas Mazzuchi",
title = "Distance-based Probabilistic Data Augmentation for
Synthetic Minority Oversampling",
journal = j-TDS,
volume = "2",
number = "4",
pages = "40:1--40:??",
month = nov,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3510834",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Fri Aug 25 12:23:02 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3510834",
abstract = "Class imbalance can adversely affect the performance
of machine learning for prediction and classification.
One approach to address the class imbalance \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "",
articleno = "40",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Ahmed:2021:SAP,
author = "Shibbir Ahmed and Md Johirul Islam and Hridesh Rajan",
title = "Semantics and Anomaly Preserving Sampling Strategy for
Large-Scale Time Series Data",
journal = j-TDS,
volume = "2",
number = "4",
pages = "41:1--41:??",
month = nov,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3511918",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Fri Aug 25 12:23:02 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3511918",
abstract = "We propose PASS, a O ( n ) algorithm for data
reduction that is specifically aimed at preserving the
semantics of time series data visualization in the form
of line \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "",
articleno = "41",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Gan:2021:TRM,
author = "Wensheng Gan and Guoting Chen and Hongzhi Yin and
Philippe Fournier-Viger and Chien-Ming Chen and Philip
S. Yu",
title = "Towards Revenue Maximization with Popular and
Profitable Products",
journal = j-TDS,
volume = "2",
number = "4",
pages = "42:1--42:??",
month = nov,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3488058",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Fri Aug 25 12:23:02 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3488058",
abstract = "Economic-wise, a common goal for companies conducting
marketing is to maximize the return revenue/profit by
utilizing the various effective \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "",
articleno = "42",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Dutta:2021:BDC,
author = "Hridoy Sankar Dutta and Tanmoy Chakraborty",
title = "Blackmarket-Driven Collusion on Online Media: a
Survey",
journal = j-TDS,
volume = "2",
number = "4",
pages = "43:1--43:??",
month = nov,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3517931",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Fri Aug 25 12:23:02 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3517931",
abstract = "Online media platforms have enabled users to connect
with individuals and organizations, and share their
thoughts. Other than connectivity, these \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "",
articleno = "43",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
@Article{Wang:2021:TBD,
author = "Chaoyang Wang and Zhiqiang Guo and Jianjun Li and
Guohui Li and Peng Pan",
title = "A Text-based Deep Reinforcement Learning Framework
Using Self-supervised Graph Representation for
Interactive Recommendation",
journal = j-TDS,
volume = "2",
number = "4",
pages = "44:1--44:??",
month = nov,
year = "2021",
CODEN = "????",
DOI = "https://doi.org/10.1145/3522596",
ISSN = "2691-1922",
ISSN-L = "2691-1922",
bibdate = "Fri Aug 25 12:23:02 MDT 2023",
bibsource = "http://www.math.utah.edu/pub/tex/bib/tds.bib",
URL = "https://dl.acm.org/doi/10.1145/3522596",
abstract = "Due to its nature of learning from dynamic
interactions and planning for long-run performance,
Reinforcement Learning (RL) has attracted much
attention in \ldots{}",
acknowledgement = ack-nhfb,
ajournal = "",
articleno = "44",
fjournal = "ACM Transactions on Data Science",
journal-URL = "https://dl.acm.org/loi/tds",
}
