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Covering Approximations in Set-Valued Information Systems

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Rough Sets and Knowledge Technology (RSKT 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8818))

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Abstract

As one of three basic theories of granular computing, rough set theory provides a useful tool for dealing with the granularity in information systems. Covering-based rough set theory is a generalization of this theory for handling covering data, which frequently appear in set-valued information systems. In this paper, we propose a covering in terms of attribute sets in a set-valued information system and study its responding three types of covering approximations. Moreover, we show that the covering approximation operators induced by indiscernible neighborhoods and neighborhoods are equal to the approximation operators induced by the tolerance and similarity relations, respectively. Meanwhile, the covering approximation operators induced by complementary neighborhoods are equal to the approximation operators induced by the inverse of the similarity relation. Finally, by introducing the concept of relational matrices, the relationships of these approximation operators are equivalently represented.

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Author information

Authors and Affiliations

  1. Lab of Granular Computing, Minnan Normal University, Zhangzhou, China

    Yanqing Zhu & William Zhu

Authors
  1. Yanqing Zhu
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  2. William Zhu
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Editor information

Editors and Affiliations

  1. Tongji University, Shanghai, China

    Duoqian Miao

  2. Department of Electrical and Computer En, University of Alberta, Edmonton, Alberta, Canada

    Witold Pedrycz

  3. University of Warsaw, Warsaw, Poland

    Dominik Ślȩzak

  4. University of Applied Sciences, München, Germany

    Georg Peters

  5. Tianjin University, Tianjin, China

    Qinghua Hu

  6. Tongji University, Shanghai, China

    Ruizhi Wang

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© 2014 Springer International Publishing Switzerland

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Zhu, Y., Zhu, W. (2014). Covering Approximations in Set-Valued Information Systems. In: Miao, D., Pedrycz, W., Ślȩzak, D., Peters, G., Hu, Q., Wang, R. (eds) Rough Sets and Knowledge Technology. RSKT 2014. Lecture Notes in Computer Science(), vol 8818. Springer, Cham. https://doi.org/10.1007/978-3-319-11740-9_61

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  • DOI: https://doi.org/10.1007/978-3-319-11740-9_61

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11739-3

  • Online ISBN: 978-3-319-11740-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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