| Formal Concept Analysis is an efficient tool of data analysis and knowledge processing. It is formulated based on the notion of a formal context specifying which objects posses what properties or attributes. A formal concept is defined as a pair of a set of objects and a set of properties connected by two set-theoretic operators. As an efficient mathematical tool of data analysis and knowledge processing, FCA has been applied in many fields, such as knowledge engineering, data mining, information searches, and software engineering.In FCA, most scholars are dedicated in the study of exact concepts in formal context. In view of data analysis, each subset of the universe can be looked upon an extension of a formal concept, some of them for exact concepts, and others for inexact concepts. In this paper, we conduct a further study on the uncertain concepts and fuzzy concepts in the formal context. The major achievements are as follows:1 Based on covering rough set approximation operators, the approximations of uncertain concepts are described. The accuracy degrees of uncertain concepts are presented.2 Based on the exact formal concepts, a fuzzy similarity relation between objects is presented and a fuzzy rough approximation space is constructed. Based on fuzzy rough approximation operators, the approximations of fuzzy concepts in the universe are described. The accuracy degrees of fuzzy concepts are constructed.3 The fuzzy similarity relations between objects with respect to attribute oriented concept lattice and object oriented concept lattice are proposed. Based on fuzzy rough approximation operators, the accuracy degrees of fuzzy concepts are characterized. |
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