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Query Expansion Using Augmented Terms in an Extended Boolean Model
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  • Query Expansion Using Augmented Terms in an Extended Boolean Model
  • Query Expansion Using Augmented Terms in an Extended Boolean Model
저자명
Nguyen. Tuan-Quang,Heo. Jun-Seok,Lee. Jung-Hoon,Kim. Yi-Reun,Whang. Kyu-Young
간행물명
Journal of computing science and engineering
권/호정보
2008년|2권 1호|pp.26-43 (18 pages)
발행정보
한국정보과학회
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

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.