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A Study on Improving the Effectiveness of Information Retrieval Through P-norm, RF, LCAF
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  • A Study on Improving the Effectiveness of Information Retrieval Through P-norm, RF, LCAF
  • A Study on Improving the Effectiveness of Information Retrieval Through P-norm, RF, LCAF
저자명
Kim. Young-cheon,Lee. Sung-joo
간행물명
International journal of fuzzy logic and intelligent systems
권/호정보
2002년|2권 1호|pp.9-14 (6 pages)
발행정보
한국지능시스템학회
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정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

Boolean retrieval is simple and elegant. However, since there is no provision for term weighting, no ranking of the answer set is generated. As a result, the size of the output might be too large or too small. Relevance feedback is the most popular query reformulation strategy. in a relevance feedback cycle, the user is presented with a list of the retrieved documents and, after examining them, marks those which are relevant. In practice, only the top 10(or 20) ranked documents need to be examined. The main idea consists of selecting important terms, or expressions, attached to the documents that have been identified as relevant by the user, and of enhancing the importance of these terms in a new query formulation. The expected effect is that the new query will be moved towards the relevant documents and away from the non-relevant ones. Local analysis techniques are interesting because they take advantage of the local context provided with the query. In this regard, they seem more appropriate than global analysis techniques. In a local strategy, the documents retrieved for a given query q are examined at query time to determine terms for query expansion. This is similar to a relevance feedback cycle but might be done without assistance from the user.