Query expansion using augmented terms in an extended boolean model = 확장 불리언 모델에서 추가용어를 이용한 질의 확장

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dc.contributor.advisorWhang, Kyu-Young-
dc.contributor.advisor황규영-
dc.contributor.authorNguyen, Tuan Quang-
dc.date.accessioned2011-12-13T06:06:21Z-
dc.date.available2011-12-13T06:06:21Z-
dc.date.issued2007-
dc.identifier.urihttp://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=265029&flag=dissertation-
dc.identifier.urihttp://hdl.handle.net/10203/34748-
dc.description학위논문(석사) - 한국과학기술원 : 전산학전공, 2007.2, [ vi, 32 p. ]-
dc.description.abstractWe 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 that have 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.eng
dc.languageeng-
dc.publisher한국과학기술원-
dc.subjectExtended Boolean Model-
dc.subjectSearch Engine-
dc.subjectQuery Expansion-
dc.subject질의 확장-
dc.subject확장 불리언 모델-
dc.subject검색 엔진-
dc.subjectTerm Reweighting-
dc.titleQuery expansion using augmented terms in an extended boolean model = 확장 불리언 모델에서 추가용어를 이용한 질의 확장-
dc.typeThesis(Master)-
dc.identifier.CNRN265029/325007 -
dc.description.department한국과학기술원 : 전산학전공, -
dc.identifier.uid020054314-
dc.contributor.localauthorWhang, Kyu-Young-
dc.contributor.localauthor황규영-
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CS-Theses_Master(석사논문)
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