2006 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops
Incomplete Information Systems Processing Based on Fuzzy-Clustering
Hong Kong, China
December 18-December 22
ISBN: 0-7695-2749-3
Qinghua Zhang, Southwest Jiaotong University, China; Chongqing University of Posts and Telecommunications, China
Guoyin Wang, Southwest Jiaotong University, China; Chongqing University of Posts and Telecommunications, China
Jun Hu, Chongqing University of Posts and Telecommunications, China
Xianquan Liu, Southwest Jiaotong University, China; Chongqing University of Posts and Telecommunications, China
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.
Citation:
Qinghua Zhang, Guoyin Wang, Jun Hu, Xianquan Liu, "Incomplete Information Systems Processing Based on Fuzzy-Clustering," wi-iatw, pp.486-489, 2006 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops, 2006
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