Matrix Computation for Concept Lattices
Rough set theory and Formal concept analysis (FCA) can be viewed as two different approaches of data analysis on data description and summarization. They focus on different characteristics of data in a context: the Indiscernibility relation and the binary relation. The indiscemibility of objects with respect to a set of properties is an important notion in rough set theory. In general, this relation is an equivalence relation. A matrix can be seen as an internal representation of equivalence relations. The binary relation in FCA can establish contact with matrix through rough set theory. Representing knowledge in a form of matrix has many advantages. For examples, to represent knowledge in a form of a discernibility matrix enable simple computation of the core, reducts, etc. In this paper, this approach is first applied to FCA. Concept lattices are expressed in terms of matrices that can be computed intuitively and efficiently.
Rough sets equivalence relations matrices concept lattices.
Qiang Wu Zongtian Liu Baisheng Shi
Department of Computer Science, ShaoXing University, Zhejiang, China;School of Computer Engineering School of Computer Engineering and Science, Shanghai University, No. 149, Rd.Yanchang, Shanghai, Chi
国际会议
Firth IEEE International Conference on Cognitive Informatics(第五届认知信息国际会议)
北京
英文
696-700
2006-07-17（万方平台首次上网日期，不代表论文的发表时间）