Entry Lee:2008:BCQ from talip.bib

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BibTeX entry

@Article{Lee:2008:BCQ,
  author =       "Cheng-Wei Lee and Min-Yuh Day and Cheng-Lung Sung and
                 Yi-Hsun Lee and Tian-Jian Jiang and Chia-Wei Wu and
                 Cheng-Wei Shih and Yu-Ren Chen and Wen-Lian Hsu",
  title =        "Boosting {Chinese} Question Answering with Two
                 Lightweight Methods: {ABSPs} and {SCO-QAT}",
  journal =      j-TALIP,
  volume =       "7",
  number =       "4",
  pages =        "12:1--12:??",
  month =        nov,
  year =         "2008",
  CODEN =        "????",
  DOI =          "https://doi.org/10.1145/1450295.1450297",
  ISSN =         "1530-0226 (print), 1558-3430 (electronic)",
  ISSN-L =       "1530-0226",
  bibdate =      "Mon Dec 8 13:56:10 MST 2008",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/talip.bib",
  abstract =     "Question Answering (QA) research has been conducted in
                 many languages. Nearly all the top performing systems
                 use heavy methods that require sophisticated
                 techniques, such as parsers or logic provers. However,
                 such techniques are usually unavailable or unaffordable
                 for under-resourced languages or in resource-limited
                 situations. In this article, we describe how a
                 top-performing Chinese QA system can be designed by
                 using lightweight methods effectively. We propose two
                 lightweight methods, namely the Sum of Co-occurrences
                 of Question and Answer Terms (SCO-QAT) and
                 Alignment-based Surface Patterns (ABSPs). SCO-QAT is a
                 co-occurrence-based answer-ranking method that does not
                 need extra knowledge, word-ignoring heuristic rules, or
                 tools. It calculates co-occurrence scores based on the
                 passage retrieval results. ABSPs are syntactic patterns
                 trained from question-answer pairs with a multiple
                 alignment algorithm. They are used to capture the
                 relations between terms and then use the relations to
                 filter answers. We attribute the success of the ABSPs
                 and SCO-QAT methods to the effective use of local
                 syntactic information and global co-occurrence
                 information.\par

                 By using SCO-QAT and ABSPs, we improved the RU-Accuracy
                 of our testbed QA system, ASQA, from 0.445 to 0.535 on
                 the NTCIR-5 dataset. It also achieved the top 0.5
                 RU-Accuracy on the NTCIR-6 dataset. The result shows
                 that lightweight methods are not only cheaper to
                 implement, but also have the potential to achieve
                 state-of-the-art performances.",
  acknowledgement = ack-nhfb,
  articleno =    "12",
  fjournal =     "ACM Transactions on Asian Language Information
                 Processing",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?&idx=J820",
  keywords =     "answer filtering; answer ranking; Chinese question
                 answering; co-occurrence; lightweight method; surface
                 pattern",
}

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