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基于形式概念分析的用户查询词与网页匹配方法(英文)

The Method of Matching User Queries with Web Pages Based on FCA
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摘要 当前,搜索引擎是人们从Web上获取信息的主要工具,当用户给搜索引擎一些查询词后,搜索引擎会返回大量的用户不感兴趣的网页。为了解决这一问题,本文从自动推理的角度,提出了一个用户查询词与网页匹配模型。该摸型利用形式概念分析基本理论,提出了OR_RULE和AND_RULE,分别讨论了这些关联规则和用户查询的最小形式概念,并建立了OR_MATCH和ANF_MATCH的推理方法和算法。最后实验证明了该方法是有效的。 Nowadays,Search Engine(SE) becomes a mainstream tool that people can retrieve the useful information from internet.A searching result can be returned for submit-ting user query.However,large numbers of Web pages in the searching result are not interested by users.To overcome this problem,from automated reasoning perspec-tive,we put forward a matching model how to match user query with Web pages.According as the basic theory of formal concept lattice,we defned OR-RULE and AND-RULE,discussed the least formal concept of the user query and association rule,put forward AND-MATCH and OR-MATCH.Two reasoning methods based on AND-MATCH and OR-MATCH,their algorithms of the matching model,are proposed.The experiment demonstrates that these method is e±cient.
作者 杜亚军
出处 《西华大学学报(自然科学版)》 CAS 2008年第6期38-48,共11页 Journal of Xihua University:Natural Science Edition
基金 the National Natural Science Foundation(Grant 600872089)
关键词 搜索引擎 匹配模型 形式概念分析 不确定性推理 网页匹配 search engine matching model formal concept analyse uncertainty reasoning Web page matching
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  • 1[1]A.Bookstein.Fuzzy requests:An Approach to Weighted Boolean Searches[J].Journal of the American Society for Information Science,1980,31 (4):240-247,
  • 2[2]A.Savasere,E.Omiecinski,S.Navathe.An Effcient Algorithm for Mining Association Rules in Large Databases[M].Proceedings of Very Large Data Bases,.Zurich,Switzerland.1995:432-443.
  • 3[3]C.Carpineto,G.Romano.Exploiting the Potential of Concept Lattices for Information Retrieval with CREDO[J].Journal of Universal Computer Science.2004,10(8):985-1013.
  • 4[4]C.Lindig.Concept-Based Component Retrieval[J].The proceedings of International Joint Conference on Artifeial Intelligence.1995:21-25.
  • 5[5]D.Crouch,C.Crouch,D.Andreas.The Use of Cluster Hierarchies in Hypertext Information Retrieval[M].Hypertext89 Proceeding.Pittsburgh.1985 -225-237.
  • 6[6]D.E.Losada,A.Barreiro.A Logical Model for Information Retrieval Based on Propositional Logic and Belief Revision[J].British Computer Society.2001,44 (5):410-424.
  • 7[7]D.E.Loseda,J.M.F.Luna.Advances in Information Retrieval.The Proceeding of the 27th European Conference on Information Retrieval Research[C].Lecture Notes in Computer Science.Springer Verlag.2005.
  • 8[8]G.Bordogna,G.Pasi.A Fuzzy Linguistic Approach Generalizing Boolean Information Retrieval:A Model and Its Evaluation[J].Journal of the American Society for Information Science.1993,44(2):70-82.
  • 9[9]G.Salton.Developments in Automatic Text Retrieval[J].Science,1991,253(30):974-980.
  • 10[10]G.Salton,A.Wang,C.S.Yang.A Vector Space Model for Automatic Indexing[C].Communication of the ACM,1975,18(11):613-620.

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