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Approximate Boolean Reasoning Approach to Rough Sets and Data Mining

  • Conference paper
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

Many problems in rough set theory have been successfully solved by boolean reasoning (BR) approach. The disadvantage of this elegant methodology is based on its high space and time complexity. In this paper we present a modified BR approach that can overcome those difficulties. This methodology is called the approximate boolean reasoning (ABR) approach. We summarize some most recent applications of ABR approach in development of new efficient algorithms in rough sets and data mining.

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Author information

Authors and Affiliations

  1. Institute of Mathematics, Warsaw University, Banacha 2, 02-097, Warsaw, Poland

    Hung Son Nguyen

Authors
  1. Hung Son Nguyen
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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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Nguyen, H.S. (2005). Approximate Boolean Reasoning Approach to Rough Sets and Data Mining. 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_2

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  • DOI: https://doi.org/10.1007/11548706_2

  • 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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