A Fuzzy FCA-based Approach to Conceptual Clustering for Automatic Generation of Concept Hierarchy on Uncertainty Data

Abstract

Abstract. This paper proposes a new fuzzy FCA-based approach to conceptual clustering for automatic generation of concept hierarchy on uncertainty data. The proposed approach first incorporates fuzzy logic into Formal Concept Analysis (FCA) to form a fuzzy concept lattice. Next, a fuzzy conceptual clustering technique is proposed to cluster the fuzzy concept lattice into conceptual clusters. Then, hierarchical relations are generated among conceptual clusters for constructing the concept hierarchy. In this paper, we also apply the proposed approach to generate a concept hierarchy of research areas from a citation database. The performance of the proposed approach is also discussed in the paper.