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2001•Journal of Tsinghua University(Science and Technology)Requires access

Advances in rough set theory and its appliations

Keyun Hu

Open publisher page 4 citations

Abstract

Rough set theory, a new mathematical tool dealing with vagueness and uncertainty, was introduced by Pawlak in 1982. It has been widely used in the area of AI, data mining, pattern recognition, fault diagnositics, etc. This paper describes the basic algorithms for rough set theory, including equivalent relation, upper/lower approximation and reduction. Then several extensions of rough set theory are discussed such as VPRS, similarity based model, and applications of rough set theory in areas like data mining, rough logic, etc. Further research directions are then discussed.

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What this paper is about

Rough set theory, a new mathematical tool dealing with vagueness and uncertainty, was introduced by Pawlak in 1982. It has been widely used in the area of AI, data mining, pattern recognition, fault diagnositics, etc. This paper describes the basic algorithms for rough set theory, including equivalent relation, upper/lower approximation and reduction. Then several extensions of rough set theory are discussed such as VPRS, similarity based model, and applications of rough set theory in areas like data mining, rough logic, etc. Further research directions are then discussed.

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Available abstract

Rough set theory, a new mathematical tool dealing with vagueness and uncertainty, was introduced by Pawlak in 1982. It has been widely used in the area of AI, data mining, pattern recognition, fault diagnositics, etc. This paper describes the basic algorithms for rough set theory, including equivalent relation, upper/lower approximation and reduction. Then several extensions of rough set theory are discussed such as VPRS, similarity based model, and applications of rough set theory in areas like data mining, rough logic, etc. Further research directions are then discussed.

Key concepts: Rough set, Vagueness, Dominance-based rough set approach, Set theory, Data mining, Relation (database), Set (abstract data type), Reduction (mathematics)

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