DOI QR코드

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Query Expansion Using Augmented Terms in an Extended Boolean Model

  • Nguyen, Tuan-Quang (Department of Computer Science Korea Advanced Institute of Science and Technology(KAIST)) ;
  • Heo, Jun-Seok (Department of Computer Science Korea Advanced Institute of Science and Technology(KAIST)) ;
  • Lee, Jung-Hoon (Department of Computer Science Korea Advanced Institute of Science and Technology(KAIST)) ;
  • Kim, Yi-Reun (Department of Computer Science Korea Advanced Institute of Science and Technology(KAIST)) ;
  • Whang, Kyu-Young (Department of Computer Science Korea Advanced Institute of Science and Technology(KAIST))
  • 발행 : 2008.03.31

초록

We propose a new query expansion method in the extended Boolean model that improves precision without degrading recall. For improving precision, our method promotes the ranks of documents having more query terms since users typically prefer such documents. The proposed method consists of the following three steps: (1) expanding the query by adding new terms related to each term of the query, (2) further expanding the query by adding augmented terms, which are conjunctions of the terms, (3) assigning a weight on each term so that augmented terms have higher weights than the other terms. We conduct extensive experiments to show the effectiveness of the proposed method. The experimental results show that the proposed method improves precision by up to 102% for the TREC-6 data compared with the existing query expansion method using a thesaurus proposed by Kwon et al.

키워드

참고문헌

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피인용 문헌

  1. Selective sampling techniques for feedback-based data retrieval vol.22, pp.1-2, 2011, https://doi.org/10.1007/s10618-010-0168-8