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Searching Decision Rules in Very Large Databases Using Rough Set Theory

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Rough Sets and Current Trends in Computing (RSCTC 2000)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2005))

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Abstract

This paper applies rough set theory to find decision rules using ORACLE RDBMS. The major steps include elimination of redundant attributes and of redundant attribute values for each tuple. In this paper three algorithms to extract high frequency decision rules from very large decision tables are presented. One algorithm uses pure SQL syntax. The other two use sorting algorithm and binary tree data structure respectively. The performances among these methods are evaluated and compared. The use of binary tree structure improves the computational time tremendously. So pure SQL results indicate some major change to query optimizer may be desirable if it will be used for data mnining.

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References

  1. Z. Pawlak. Rough Sets: Theoretical Aspects of Reasoning about Data, Kluwer Academic, Dordrecht (1991)

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  2. T. Y. Lin, “Rough Set Theory in Very Large Databases,” Symposium on Modeling, Analysis and Simulation, IMACS Multi Conference (Computational Engineering in Systems Applications), Lille, France, July 9-12, 1996, Vol. 2 of 2, 936–941.

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  3. T. Y. Lin. “An Overview of Rough Set Theory from the Point of View of Relational Databases,” Bulletin of International Rough Set Society, vol. 1, no. 1, March 1997.

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  4. R. Agrawal, R. Srikant. “Fast Algorithms for Mining Association Rules,” in Proceeding of 20th VLDB Conference San Tiago, Chile, 1994.

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Author information

Authors and Affiliations

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

    Tsau Young (“T.Y.”) Lin & Tsau Young (“T.Y.”) Lin

  2. Berkeley Initiative in Soft Computing, University of California, Berkeley, 94720, California

    Hui Cao

Authors
  1. Tsau Young (“T.Y.”) Lin
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  2. Hui Cao
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Editor information

Editors and Affiliations

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

    Wojciech Ziarko  & Yiyu Yao  & 

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© 2001 Springer-Verlag Berlin Heidelberg

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Young (“T.Y.”) Lin, T., Cao, H. (2001). Searching Decision Rules in Very Large Databases Using Rough Set Theory. In: Ziarko, W., Yao, Y. (eds) Rough Sets and Current Trends in Computing. RSCTC 2000. Lecture Notes in Computer Science(), vol 2005. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45554-X_42

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  • DOI: https://doi.org/10.1007/3-540-45554-X_42

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43074-2

  • Online ISBN: 978-3-540-45554-7

  • eBook Packages: Springer Book Archive

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