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Erschienen in:
2006 | OriginalPaper | Buchkapitel
A Novel Approach to Attribute Reduction in Concept Lattices
verfasst von : Xia Wang, Jianmin Ma
Erschienen in: Rough Sets and Knowledge Technology
Verlag: Springer Berlin Heidelberg
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Concept lattice is an effective tool for data analysis and knowledge discovery. Since one of the key problems of knowledge discovery is knowledge reduction, it is very necessary to look for a simple and effective approach to knowledge reduction. In this paper, we develop a novel approach to attribute reduction by defining a partial relation and partial classes to generate concepts and introducing the notion of meet-irreducible element in concept lattice. Some properties of meet-irreducible element are presented. Furthermore, we analyze characteristics of attributes and obtain sufficient and necessary conditions of the characteristics of attributes. In addition, we illustrate that adopting partial classes to generate concepts and the approach to attribute reduction are simpler and more convenient compared with current approaches.