Effectiveness of Passage-Based Document Retrieval for Short Queries

18 References
  • KISE Koichi
    Dept. of Computer and Systems Sciences, Graduate School of Engineeirng, Osaka Prefecture University
  • JUNKER Markus
    German Research Center for Artificial Intelligence(DFKI)
  • DENGEI Andreas
    German Research Center for Artificial Intelligence(DFKI)
  • MATSUMOTO Keinosuke
    Dept. of Computer and Systems Sciences, Graduate School of Engineeirng, Osaka Prefecture University

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Description

Document retrieval is a fundamental but important task for intelligent access to a huge amount of information stored in documents. Although the history of its research is long, it is still a hard task especially in the case that lengthy documents are retrieved with very short queries (a few keywords). For the retrieval of long documents, methods called passage-based document retrieval have proven to be effective. In this paper, we experimentally show that a passage-based method based on window passages is also effective for dealing with short queries on condition that documents are not too short. We employ a method called "density distributions" as a method based on window passages, and compare it with three conventional methods : the simple vector space model, pseudo relevance feedback and latent semantic indexing. We also compare it with a passage-based method based on discourse passages.

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Details 詳細情報について

  • CRID
    1572543026836951808
  • NII Article ID
    110004069199
  • NII Book ID
    AA10826272
  • ISSN
    09168532
  • Text Lang
    en
  • Data Source
    • CiNii Articles

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