A New Rough Sets Model Based on Database Systems

  • Xiaohua Tony Hu
  • T. Y. Lin
  • Jianchao Han
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2639)


In this paper we present a new rough sets model based on database systems. We borrow the main ideas of the original rough sets theory and redefine them based on the database theory to take advantage of the very efficient set-oriented database operation. We present a new set of algorithms to calculate core, reduct based on our new database based rough set model. Almost all the operations used in generating core, reduct in our model can be performed using the database set operations such as Count, Projection. Our new rough sets model is designed based on database set operations, compared with the traditional rough set models, ours is very efficient and scalable.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    Cercone N., Ziarko W., Hu X., Rule Discovery from Databases: A Decision Matrix Approach, Methodologies for Intelligent System, Ras Zbigniew, Zemankova Maria (eds), 1996Google Scholar
  2. [2]
    Hu, X., Cercone N., Han, J., Ziarko, W, GRS: A Generalized Rough Sets Model, in Data Mining, Rough Sets and Granular Computing, T.Y. Lin, Y.Y. Yao and L. Zadeh (eds), Physica-VerlagGoogle Scholar
  3. [3]
    John, G., Kohavi, R., Pfleger, K., Irrelevant Features and the Subset Selection Problem, In Proc. ML-94, 1994Google Scholar
  4. [4]
    Kira, K.; Rendell, L.A. The feature Selection Problem: Traditional Methods and a New Algorithm, In Proc. AAAI-92Google Scholar
  5. [5]
    Kumar A., A New Technique for Data Reduction in A Database System for Knowledge Discovery Applications, Journal of Intelligent Systems, 10(3)Google Scholar
  6. [6]
    Lin T.Y., Yao Y.Y. Zadeh L. (eds), Data Mining, Rough Sets and Granular Computing, Physica-Verlag, 2002Google Scholar
  7. [7]
    T. Y. Lin, H. Cao, “Searching Decision Rules in Very Large Databases using Rough Set Theory.” In Rough sets and Current Trends in Computing, Ziarko & Yao (eds)Google Scholar
  8. [8]
    Modrzejewski, M. Feature Selection Using Rough Sets Theory, in Proc. ECML-93Google Scholar
  9. [9]
    Pawlak Z., Rough Sets, International Journal of Information and Computer Science, 11(5), 1982Google Scholar
  10. [10]
    Ziarko, W., Variable Precision Rough Set Model, Journal of Computer and System Sciences, Vol. 46, No. 1, 1993Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Xiaohua Tony Hu
    • 1
  • T. Y. Lin
    • 2
  • Jianchao Han
    • 3
  1. 1.College of Information Science and TechnologyDrexel UniversityPhiladelphia
  2. 2.Dept. of Computer ScienceSan Jose State UniversitySan Jose
  3. 3.Dept. of Computer ScienceCalifornia State UniversityDominguez Hills

Personalised recommendations