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New Technology of Library and Information Service  2008, Vol. 24 Issue (8): 53-57    DOI: 10.11925/infotech.1003-3513.2008.08.09
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The Improved Model of Web Information Retrieval Based on Fuzzy Rough Set
Fan Hongxia
(Xi’an University of Architecture & Technology  Library,   Xi’an   710055, China)
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In view of the problem that the traditional information retrieval model can’t process uncertainty knowledge perfectly, the author combines rough set and fuzzy set theory, and puts forward an improved model of Web information retrieval based on fuzzy rough set. At the same time, the author proposes a key algorithm and a performance evaluation method performonce based on the model.The model is helpful to raise efficiency of information retrieval, and is valuable both in theory and application.

Key wordsRough set      Fuzzy set      Information retrieval     
Received: 27 March 2008      Published: 25 August 2008


Corresponding Authors: Fan Hongxia     E-mail:
About author:: Fan Hongxia

Cite this article:

Fan Hongxia. The Improved Model of Web Information Retrieval Based on Fuzzy Rough Set. New Technology of Library and Information Service, 2008, 24(8): 53-57.

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[1] Richard  R J,Geatz M W.数据挖掘教程[M].翁敬农(译).北京:清华大学出版社,2003:195.
[2] Broder A Z,  Eiron N, Fontoura M, et al. Indexing Shared Content in Information Retrieval Systems[M].Springer Berlin/Heidelberg, 2006,3896:313-330.
[3] 马志辉,刘怀亮,张治国,等.基于Rough集理论的图像检索研究[J]. 情报杂志,2007,26(1):46-48.
[4] 孙红红.模糊集合理论在信息检索中的应用研究[J].现代情报,2006,26(11):160-162.
[5] Cao C, Sui Y,  Zhang Z.The Rough Logic and Roughness of Logical Theories[M]. Springer Berlin/Heidelberg, 2006,4062:610-617.
[6] 周瑛.信息检索中文本相似度的研究[J].情报理论与实践,2005,28(2):142-144.
[7] 安兴茹,周咏仪.检索效果评价的数学模型研究[J].情报杂志,2007,26(1):61-63,66.

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