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Extract Rule from Generalized Rough Approximate Space Based on Generalized Concept Lattice
基于广义概念格的广义粗近似空间中规则的发现与提取

Keywords: Generalized rough approximation space,Concept lattice,Generalized similarity relation,Support (confidence) degree,Interesting measure
粗集理论
,广义概念格,广义粗近似空间,规则提取,人工智能

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Abstract:

This paper proposes a new method of constructing generalized concept lattice and producing rules from it in the generalized rough approximate space based on generalized similar relation which is more extensive than equivalent relation. Finally, a simple algorithm is presented to extract rules based on interesting measure.

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