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Annual Conference of the Japanese Society for Artificial Intelligence

JSAI 2001: New Frontiers in Artificial Intelligence pp 311–315Cite as

Generalization of Rough Sets with α-Coverings of the Universe Induced by Conditional Probability Relations

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2253))

Abstract

Standard rough sets are defined by a partition induced by an equivalence relation representing discernibility of elements. Equivalence relations may not provide a realistic view of relationships between elements in real-world applications. One may use coverings of, or non-equivalence relations on, the universe. In this paper, the notion of weak fuzzy similarity relations, a generalization of fuzzy similarity relations, is used to provide a more realistic description of relationships between elements. A special type of weak fuzzy similarity relations called conditional probability relation is discussed. Generalized rough set approximations are proposed by using α-coverings of the universe induced by conditional probability relations.

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References

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Author information

Authors and Affiliations

  1. Meiji University, Kawasaki-shi, Kanagawa-ken, Japan

    Rolly Intan & Masao Mukaidono

  2. University of Regina, S4S 0A2, Regina, Saskatchewan, Canada

    Y. Y. Yao

Authors
  1. Rolly Intan
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  2. Masao Mukaidono
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  3. Y. Y. Yao
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Editor information

Editors and Affiliations

  1. Graduate School of Business Science, The University of Tsukuba, Tokyo

    Takao Terano  & Yukio Ohsawa  & 

  2. School of Engineering, The University of Tokyo, Tokyo

    Toyoaki Nishida

  3. Dept.of Computer Science, National Defense Academy, Japan

    Akira Namatame

  4. School of Medicines, Shimane Medical University, Japan

    Syusaku Tsumoto

  5. The Institute of Scientific and Industrial Research, Osaka University, Osaka

    Takashi Washio

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© 2001 Springer-Verlag Berlin Heidelberg

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Intan, R., Mukaidono, M., Yao, Y.Y. (2001). Generalization of Rough Sets with α-Coverings of the Universe Induced by Conditional Probability Relations. In: Terano, T., Ohsawa, Y., Nishida, T., Namatame, A., Tsumoto, S., Washio, T. (eds) New Frontiers in Artificial Intelligence. JSAI 2001. Lecture Notes in Computer Science(), vol 2253. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45548-5_37

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  • DOI: https://doi.org/10.1007/3-540-45548-5_37

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43070-4

  • Online ISBN: 978-3-540-45548-6

  • eBook Packages: Springer Book Archive

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