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International Workshop on Rough Sets, Fuzzy Sets, Data Mining, and Granular-Soft Computing

RSFDGrC 2013: Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing pp 157–168Cite as

A Fuzzy Rough Set Approach for Incrementally Updating Approximations in Hybrid Information Systems

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8170))

Abstract

In real-applications, there may exist missing data and many kinds of data (e.g., categorical, real-valued and set-valued data) in an information system which is called as a Hybrid Information System (HIS). A new Hybrid Distance (HD) between two objects in HIS is developed based on the value difference metric. Then, a novel fuzzy rough set is constructed by using the HD distance and the Gaussian kernel. In addition, the information systems often vary with time. How to use the previous knowledge to update approximations in fuzzy rough sets is a key step for its applications on hybrid data. The fuzzy information granulation methods based on the HD distance are proposed. Furthermore, the principles of updating approximations in HIS under the variation of the attribute set are discussed. A fuzzy rough set approach for incrementally updating approximations is then presented. Some examples are employed to illustrate the proposed methods.

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Author information

Authors and Affiliations

  1. School of Information Science and Technology, Southwest Jiaotong University, Chengdu, 610031, China

    Anping Zeng, Tianrui Li, Chuan Luo, Junbo Zhang & Yan Yang

  2. School of Computer and Information Engineering, Yibin University, Yibin, 644007, China

    Anping Zeng

Authors
  1. Anping Zeng
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  2. Tianrui Li
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  3. Chuan Luo
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  4. Junbo Zhang
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  5. Yan Yang
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Editor information

Editors and Affiliations

  1. University of Milano-Bicocca, viale Sarca 336/14, 20126, Milano, Italy

    Davide Ciucci

  2. Osaka University, 560-8531, Toyonaka, Osaka, Japan

    Masahiro Inuiguchi

  3. University of Regina, S4S 0A2, Regina, SK, Canada

    Yiyu Yao

  4. University of Warsaw, ul. Banacha, 2, 02-097, Warsaw, Poland

    Dominik Ślęzak

  5. Chongqing Institute of Green and Intelligent Technology, CAS, 401122, Chongqing, China

    Guoyin Wang

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© 2013 Springer-Verlag Berlin Heidelberg

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Zeng, A., Li, T., Luo, C., Zhang, J., Yang, Y. (2013). A Fuzzy Rough Set Approach for Incrementally Updating Approximations in Hybrid Information Systems. In: Ciucci, D., Inuiguchi, M., Yao, Y., Ślęzak, D., Wang, G. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2013. Lecture Notes in Computer Science(), vol 8170. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41218-9_17

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  • DOI: https://doi.org/10.1007/978-3-642-41218-9_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-41217-2

  • Online ISBN: 978-3-642-41218-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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