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

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 rela- tions are generated among conceptual clusters for constructing the con- cept 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.