Incomplete Information Systems Processing Based on Fuzzy-Clustering

Authors:
Qinghua Zhang;Guoyin Wang;Jun Hu;Xianquan Liu
Affiliations:
Southwest Jiaotong University, China/ Chongqing University of Posts and Telecommunications, China;Southwest Jiaotong University, China/ Chongqing University of Posts and Telecommunications, China;Chongqing University of Posts and Telecommunications, China;Southwest Jiaotong University, China/ Chongqing University of Posts and Telecommunications, China
Venue:
WI-IATW '06 Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology
Year:
2006

Citing 3
Cited 1

Rough set approach to incomplete information systems

Information Sciences: an International Journal
Rules in incomplete information systems

Information Sciences: an International Journal
Uncertainty Measure of Covering Generated Rough Set

WI-IATW '06 Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology

Research on rough set theory and applications in China

Transactions on rough sets VIII

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Abstract

The classical rough set theory developed by Prof. Z.Pawlak can't process incomplete information systems directly. A new method based on fuzzy-clustering is proposed in this paper. The nonequivalence relation defined in incomplete information systems is transformed into an equivalence relation at first, then the variable upper-approximation, variable lower-approximation and variable positive region are developed using the classical rough set theory. Finally, the relations between our method and several other extended rough set models are studied.