Entry Fukumoto:2008:ICL from talip.bib

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BibTeX entry

@Article{Fukumoto:2008:ICL,
  author =       "Fumiyo Fukumoto and Yoshimi Suzuki",
  title =        "Integrating Cross-Language Hierarchies and Its
                 Application to Retrieving Relevant Documents",
  journal =      j-TALIP,
  volume =       "7",
  number =       "3",
  pages =        "8:1--8:??",
  month =        aug,
  year =         "2008",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1386869.1386870",
  ISSN =         "1530-0226 (print), 1558-3430 (electronic)",
  ISSN-L =       "1530-0226",
  bibdate =      "Fri Aug 22 13:11:51 MDT 2008",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/talip.bib",
  abstract =     "Internet directories such as Yahoo! are an approach to
                 improve the efficacy and efficiency of Information
                 Retrieval (IR) on the Web, as pages (documents) are
                 organized into hierarchical categories, and similar
                 pages are grouped together. Most of the search engines
                 on the Web service find documents that are assigned to
                 a single classification hierarchy. Categories in the
                 hierarchy are carefully defined by human experts and
                 documents are well organized. However, a single
                 hierarchy in one language is often insufficient to find
                 all relevant material, as each hierarchy tends to have
                 some bias in both defining hierarchical structure and
                 classifying documents. Moreover, documents written in a
                 language other than the user's native language often
                 include large amounts of information related to the
                 user's request. In this article, we propose a method of
                 integrating cross-language (CL) category hierarchies,
                 that is, Reuters '96 hierarchy and UDC code hierarchy
                 of Japanese by estimating category similarities. The
                 method does not simply merge two different hierarchies
                 into one large hierarchy but instead extracts sets of
                 similar categories, where each element of the sets is
                 relevant with each other. It consists of three steps.
                 First, we classify documents from one hierarchy into
                 categories with another hierarchy using a
                 cross-language text classification (CLTC) technique,
                 and extract category pairs of two hierarchies. Next, we
                 apply $\chi^2$ statistics to these pairs to
                 obtain similar category pairs, and finally we apply the
                 generating function of the Apriori algorithm
                 (Apriori-Gen) to the category pairs, and find sets of
                 similar categories. Moreover, we examined whether
                 integrating hierarchies helps to support retrieval of
                 documents with similar contents. The retrieval results
                 showed a 42.7\% improvement over the baseline
                 nonhierarchy model, and a 21.6\% improvement over a
                 single hierarchy.",
  acknowledgement = ack-nhfb,
  articleno =    "8",
  fjournal =     "ACM Transactions on Asian Language Information
                 Processing",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?&idx=J820",
  keywords =     "cross-language hierarchies; information integration;
                 retrieval of relevant documents; text classification",
}

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