Entry Hsu:2010:MST from talip.bib

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BibTeX entry

@Article{Hsu:2010:MST,
  author =       "Chung-Chian Hsu and Chien-Hsing Chen",
  title =        "Mining Synonymous Transliterations from the {World
                 Wide Web}",
  journal =      j-TALIP,
  volume =       "9",
  number =       "1",
  pages =        "1:1--1:??",
  month =        mar,
  year =         "2010",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1731035.1731036",
  ISSN =         "1530-0226 (print), 1558-3430 (electronic)",
  ISSN-L =       "1530-0226",
  bibdate =      "Mon Mar 29 15:34:01 MDT 2010",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/talip.bib",
  abstract =     "The World Wide Web has been considered one of the
                 important sources for information. Using search engines
                 to retrieve Web pages can gather lots of information,
                 including foreign information. However, to be better
                 understood by local readers, proper names in a foreign
                 language, such as English, are often transliterated to
                 a local language such as Chinese. Due to different
                 translators and the lack of translation standard,
                 translating foreign proper nouns may result in
                 different transliterations and pose a notorious
                 headache. In particular, it may cause incomplete search
                 results. Using one transliteration as a query keyword
                 will fail to retrieve the Web pages which use a
                 different word as the transliteration. Consequently,
                 important information may be missed. We present a
                 framework for mining synonymous transliterations as
                 many as possible from the Web for a given
                 transliteration. The results can be used to construct a
                 database of synonymous transliterations which can be
                 utilized for query expansion so as to alleviate the
                 incomplete search problem. Experimental results show
                 that the proposed framework can effectively retrieve
                 the set of snippets which may contain synonymous
                 transliterations and then extract the target terms.
                 Most of the extracted synonymous transliterations have
                 higher rank of similarity to the input transliteration
                 compared to other noise terms.",
  acknowledgement = ack-nhfb,
  articleno =    "1",
  fjournal =     "ACM Transactions on Asian Language Information
                 Processing",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?&idx=J820",
  keywords =     "Chinese transliteration; cross-lingual information
                 retrieval; synonymous transliteration; text mining; Web
                 mining",
}

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