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.
This work is supported by the National 973 Program of China(2002CB31200).
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Xu, WH., Shao, MW., Zhang, WX. (2006). Knowledge Reduction Based on Evidence Reasoning Theory in Ordered Information Systems. In: Lang, J., Lin, F., Wang, J. (eds) Knowledge Science, Engineering and Management. KSEM 2006. Lecture Notes in Computer Science(), vol 4092. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11811220_45
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DOI: https://doi.org/10.1007/11811220_45
Publisher Name: Springer, Berlin, Heidelberg
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