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Frameworks for Mining Binary Relations in Data

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Rough Sets and Current Trends in Computing (RSCTC 1998)

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Abstract

This paper extends the notion of information tables and concept hierarchies of equivalence relations to binary relations. So extended rough set theory and attribute oriented generalization techniques can be used to mining binary relations in data.

partially supported by EPRI, SJSU, NASA NCC2-275, ONR N00014-96-1-0556, LLNL 442427-26449, ARO DAAH04-961-0341, and BISC at UC-Berkeley

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Author information

Authors and Affiliations

  1. Department of Mathematics and Computer Science, San Jose State University, San Jose, California, 95192

    T. Y. Lin & T. Y. Lin

  2. Department of Electric Engineering and Computer Science, University of California, Berkeley, California, 94720

    N. Zhong

  3. Department of Computer Science and Systems Engineering, Yamaguchi University, Tokiwa-Dai, 2557, Ube, 755, Japan

    J. J. Dong

  4. Department of Information and Computer Science, Waseda University, 3-4-1 Okubo Shinjuku, Tokyo, 169, Japan

    S. Ohsuga

Authors
  1. T. Y. Lin
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  2. N. Zhong
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  3. J. J. Dong
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  4. S. Ohsuga
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Editor information

Editors and Affiliations

  1. Institute of Mathematics, Warsaw University of Technology, Pl. Politechniki 1, 00-665, Warszawa, Poland

    Lech Polkowski

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

    Andrzej Skowron

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© 1998 Springer-Verlag Berlin Heidelberg

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Lin, T.Y., Zhong, N., Dong, J.J., Ohsuga, S. (1998). Frameworks for Mining Binary Relations in Data. In: Polkowski, L., Skowron, A. (eds) Rough Sets and Current Trends in Computing. RSCTC 1998. Lecture Notes in Computer Science(), vol 1424. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-69115-4_53

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  • DOI: https://doi.org/10.1007/3-540-69115-4_53

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64655-6

  • Online ISBN: 978-3-540-69115-0

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