The rough sets theory and evidence theory
Fundamenta Informaticae
Data mining using extensions of the rough set model
Journal of the American Society for Information Science - Special issue: knowledge discovery and data mining
Interpretations of belief functions in the theory of rough sets
Information Sciences: an International Journal - From rough sets to soft computing
Rough set approach to incomplete information systems
Information Sciences: an International Journal
Rules in incomplete information systems
Information Sciences: an International Journal
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Approximate Reducts and Association Rules - Correspondence and Complexity Results
RSFDGrC '99 Proceedings of the 7th International Workshop on New Directions in Rough Sets, Data Mining, and Granular-Soft Computing
Approaches to knowledge reduction based on variable precision rough set model
Information Sciences—Informatics and Computer Science: An International Journal - Mining stream data
On knowledge reduction in inconsistent decision information systems
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Attribute reduction based on evidence theory in incomplete decision systems
Information Sciences: an International Journal
On generalized fuzzy belief functions in infinite spaces
IEEE Transactions on Fuzzy Systems
Knowledge reduction in random information systems via Dempster-Shafer theory of evidence
Information Sciences: an International Journal
Knowledge reduction in incomplete information systems based on dempster-shafer theory of evidence
RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
Decision making in incomplete information system based on decision-theoretic rough sets
RSKT'11 Proceedings of the 6th international conference on Rough sets and knowledge technology
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Knowledge reduction is one of the main problems in the study of rough set theory. This paper deals with knowledge reduction in random incomplete information systems based on Dempster-Shafer theory of evidence. The concepts of random belief reducts and random plausibility reducts in random incomplete information systems are introduced. The relationships among the random belief reduct, the random plausibility reduct, and the classical reduct are examined. It is proved that, in a random incomplete information system, an attribute set is a random belief reduct if and only if it is a classical reduct, and a random plausibility consistent set must be a consistent set.