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Intelligent Information Retrieval Based on the Variable Precision Rough Set Model and Fuzzy Sets

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Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3642))

Abstract

In this paper, an information retrieval methodology and model based on variable precision rough set model (VPRSM) are proposed through combining rough sets and fuzzy sets. In the methodology, the documents are represented as fuzzy index terms, the queries are defined with a rough set and that each document has an approximation in this set. The experimental results compared with vector space model (VSM) are presented.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Technology, Xi’an Jiaotong University, Xi’an, 710049, China

    Ming He & Bo-qin Feng

Authors
  1. Ming He
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  2. Bo-qin Feng
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Regina, Regina, SK, S4S 0A2 Canada, Polish-Japanese Institute of Information Technology, Koszykowa 86, 02-008 Warsaw, P.O. Box, Poland

    Dominik Ślęzak

  2. Department of Computer Science, University of Regina, S4S 0A2, Regina, Saskatchewan, Canada

    JingTao Yao  & Wojciech Ziarko  & 

  3. Department of Electrical and Computer Engineering, University of Manitoba, R3T 5V6, Winnipeg, Manitoba, Canada

    James F. Peters

  4. College of Computer and Information Engineering, Hehan University, Henan, China

    Xiaohua Hu

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© 2005 Springer-Verlag Berlin Heidelberg

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He, M., Feng, Bq. (2005). Intelligent Information Retrieval Based on the Variable Precision Rough Set Model and Fuzzy Sets. In: Ślęzak, D., Yao, J., Peters, J.F., Ziarko, W., Hu, X. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2005. Lecture Notes in Computer Science(), vol 3642. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11548706_20

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  • DOI: https://doi.org/10.1007/11548706_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28660-8

  • Online ISBN: 978-3-540-31824-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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