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

RSFDGrC 2003: Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing pp 403–404Cite as

Deductive Data Mining

Mathematical Foundation of Database Mining

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2639))

Abstract

In ICDM02 the Foundation on Data Mining and Discovery Workshop [3], we have proposed that data mining is a procedure that transforms (extracts or discovers from) data into patterns/knowledge: Schematically

$$ DM:Patterns \Leftarrow Data, or KD:Knowledge \Leftarrow Data $$

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References

  1. T. Y. Lin and Hugo Shi, “Mathematical Foundation of Association Rules — Mining Associations by Solving Integral Linear Inequalities,” in: Data Mining and Knowledge Discovery: Theory, Tools, and Technology, Dasarathy (ed), Proceeding of SPIE, Vol. 5098, Orlando, Fl, April 21–25, 2003, to appear

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  2. T. Y. Lin, “Attribute (Feature) Completion — The Theory of Attributes from Data Mining Prospect,” in: the Proceedings of International Conference on Data Mining, Maebashi, Japan, Dec 9–12, 2002, pp. 282–289

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  3. T. Y. Lin, “Mathematical Foundation of Association Rules — Mining Associations by Solving Integral Linear Inequalities.” In the Proceedings of the Workshop on the Foundation of Data Mining and Discovery, which is a part of International Conference on Data Mining, Maebashi, Japan, Dec 9–12, 2002, pp 81–88.

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  4. T. Y. Lin, “The Power and Limit of Neural Networks,” Proceedings of the 1996 Engineering Systems Design and Analysis Conference, Montpellier, France, July 1–4, 1996, Vol. 7, 49–53.

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Author information

Authors and Affiliations

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

    Tsau Young Lin

Authors
  1. Tsau Young Lin
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Editor information

Editors and Affiliations

  1. Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, P.R. China

    Guoyin Wang

  2. Department of Computer Science, Nanchang University, Nanchang, 330029, P.R. China

    Qing Liu

  3. Department of Computer Science, University of Regina, Regina, Saskatchewan, S4S 0A2, Canada

    Yiyu Yao

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

    Andrzej Skowron

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© 2003 Springer-Verlag Berlin Heidelberg

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Lin, T.Y. (2003). Deductive Data Mining. In: Wang, G., Liu, Q., Yao, Y., Skowron, A. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2003. Lecture Notes in Computer Science(), vol 2639. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39205-X_67

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  • DOI: https://doi.org/10.1007/3-540-39205-X_67

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-14040-5

  • Online ISBN: 978-3-540-39205-7

  • eBook Packages: Springer Book Archive

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