• Title/Summary/Keyword: Similarity Relation Matrices

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Fuzzy Query Processing through Two-level Similarity Relation Matrices Construction (2계층 유사관계행렬 구축을 통한 질의 처리)

  • 이기영
    • Journal of the Korea Computer Industry Society
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    • v.4 no.10
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    • pp.587-598
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    • 2003
  • This paper construct two-level word similarity relation matrices about title and to scientific treatise. As guide keyword similarity relation matrices which is constructed to co-occurrence frequency base same time keeps recall rater by query expansion by tolerance relation, it is index structure to improve the precision rate by two-level contents base retrieval. Therefore, draw area knowledge through subject analysis and reasoned user's information request and area knowledge to fuzzy logic base. This research is research to improve vocabulary mismatch problem and information expression having essentially on query.

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A Re-Ranking Retrieval Model based on Two-Level Similarity Relation Matrices (2단계 유사관계 행렬을 기반으로 한 순위 재조정 검색 모델)

  • 이기영;은희주;김용성
    • Journal of KIISE:Software and Applications
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    • v.31 no.11
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    • pp.1519-1533
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    • 2004
  • When Web-based special retrieval systems for scientific field extremely restrict the expression of user's information request, the process of the information content analysis and that of the information acquisition become inconsistent. In this paper, we apply the fuzzy retrieval model to solve the high time complexity of the retrieval system by constructing a reduced term set for the term's relatively importance degree. Furthermore, we perform a cluster retrieval to reflect the user's Query exactly through the similarity relation matrix satisfying the characteristics of the fuzzy compatibility relation. We have proven the performance of a proposed re-ranking model based on the similarity union of the fuzzy retrieval model and the document cluster retrieval model.

Query Processing Model Using Two-level Fuzzy Knowledge Base (2단계 퍼지 지식베이스를 이용한 질의 처리 모델)

  • Lee, Ki-Young;Kim, Young-Un
    • Journal of the Korea Society of Computer and Information
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    • v.10 no.4 s.36
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    • pp.1-16
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    • 2005
  • When Web-based special retrieval systems for scientific field extremely restrict the expression of user's information request, the process of the information content analysis and that of the information acquisition become inconsistent. Accordingly, this study suggests the re-ranking retrieval model which reflects the content based similarity between user's inquiry terms and index words by grasping the document knowledge structure. In order to accomplish this, the former constructs a thesaurus and similarity relation matrix to provide the subject analysis mechanism and the latter propose the algorithm which establishes a search model such as query expansion in order to analyze the user's demands. Therefore, the algorithm that this study suggests as retrieval utilizing the information structure of a retrieval system can be content-based retrieval mechanism to establish a 2-step search model for the preservation of recall and improvement of accuracy which was a weak point of the previous fuzzy retrieval model.

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