论文信息 - A New Computation Model for Rough Set Theory Based on Database Systems

A New Computation Model for Rough Set Theory Based on Database Systems

We propose a new computation model for rough set theory using relational algebra operations in this paper. We present the necessary and sufficient conditions on data tables under which an attribute is a core attribute and those under which a subset of condition attributes is a reduct, respectively. With this model, two algorithms for core attributes computation and reduct generation are suggested. The correctness of both algorithms is proved and their time complexity is analyzed. Since relational algebra operations have been efficiently implemented in most widely-used database systems, the algorithms presented can be extensively applied to these database systems and adapted to a wide range of real-life applications with very large data sets.

[1] Z. Pawlak. Rough Sets: Theoretical Aspects of Reasoning about Data , 1991 .

[2] Maciej Modrzejewski,et al. Feature Selection Using Rough Sets Theory , 1993, ECML.

[3] Jerzy W. Grzymala-Busse,et al. Rough Sets , 1995, Commun. ACM.

[4] Xiaohua Hu,et al. Rule Discovery from Databases with Decision Matrices , 1996, ISMIS.

[5] T. Y. Lin,et al. Rough Sets and Data Mining , 1997, Springer US.

[6] David A. Bell,et al. Computational methods for rough classification and discovery , 1998, KDD 1998.

[7] Vijay V. Raghavan,et al. Feature selection and effective classifiers , 1998, KDD 1998.

[8] Jennifer Widom,et al. Database System Implementation , 2000 .

[9] L. Zadeh,et al. Data mining, rough sets and granular computing , 2002 .

[10] Tsau Young Lin,et al. A New Rough Sets Model Based on Database Systems , 2003, Fundam. Informaticae.

[11] Akhil Kumar,et al. New Techniques for Data Reduction in a Database System for Knowledge Discovery Applications , 2004, Journal of Intelligent Information Systems.