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Erschienen in:
2005 | OriginalPaper | Buchkapitel
Attribute Reduction in Concept Lattice Based on Discernibility Matrix
verfasst von : Wen-Xiu Zhang, Ling Wei, Jian-Jun Qi
Erschienen in: Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing
Verlag: Springer Berlin Heidelberg
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As an effective tool for knowledge discovery, concept lattice has been successfully applied to various fields. One of the key problems of knowledge discovery is knowledge reduction. This paper studies attribute reduction in concept lattice. Using the idea similar to Skowron and Rauszer’s discernibility matrix, the discernibility matrix and function of a concept lattice are defined. Based on discernibility matrix, an approach to attribute reduction in concept lattice is presented, and the characteristics of core attribute are analyzed.