Granule Description of Object (Attribute)-Oriented Linguistic Concept Lattice Based on Dominance Relation

Concept lattice, as an effective tool for knowledge acquisition and data analysis, has been successfully used in many fields. Aiming at the problem of groups for uncertain information in the linguistic environment, this paper mainly focuses on the granule description with linguistic concept lattice from the two aspects of object-oriented and attribute-oriented. Specifically, we present an object-oriented linguistic concept lattice to describe the linguistic dominance relation between attributes, the corresponding attribute dominant class is obtained meanwhile. Furthermore, we devote to constructing an object-oriented linguistic granular concept lattice by using the equivalence relations on the set of objects, combining the idea of granular computing. In order to deal with the linguistic information under the different importance of objects, the notion of attribute-oriented linguistic concept lattice based on object dominance relation is put forward. What’s more, we classify the attribute set so as to generate the attribute-oriented linguistic granular concepts with respect to a set of attributes. Besides, the effectiveness of the object-oriented linguistic concept lattice, object-oriented linguistic granular concept lattice, attribute-oriented linguistic concept lattice, attribute-oriented linguistic granular concept lattice is illustrated by the comparative analysis with other methods.