Knowledge reduction based on evidence reasoning theory in ordered information systems

Authors:
Wei-Hua Xu;Ming-Wen Shao;Wen-Xiu Zhang
Affiliations:
Faculty of Science, Institute for Information and System Sciences, Xi’an Jiaotong University, Xi’an, Shaan’xi, P.R. China;School of Information Technology, Jiangxi University of Finance & Economics, Nanchang, Jiangxi, P.R. China;Faculty of Science, Institute for Information and System Sciences, Xi’an Jiaotong University, Xi’an, Shaan’xi, P.R. China
Venue:
KSEM'06 Proceedings of the First international conference on Knowledge Science, Engineering and Management
Year:
2006

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Abstract

Rough set theory has been considered as a useful tool to model the vagueness, imprecision, and uncertainty, and has been applied successfully in many fields. Knowledge reduction is one of the most important problems in rough set theory. However, in real-world most of information systems are based on dominance relations in stead of the classical rough set because of various factors. To acquire brief decision rules from systems based on dominance relations, knowledge reductions are needed. The main aim of this paper is to study the problem. The basic concepts and properties of knowledge reduction based on evidence reasoning theory are discussed. Furthermore, the characterization and knowledge reduction approaches based on evidence reasoning theory are obtained with examples in several kinds of ordered information system, which is every useful in future research works of the ordered information systems.