A FCA-based approach for enriching users´ knowledge base

Despite of the various benefits obtainable from Formal Concept Analysis (FCA) in knowledge base construction, FCA-based approaches are not enough to help an expert enrich his knowledge. This is because they provide only the clusters constructed with user-defined knowledge and super-sub relation between the clusters. In this paper, we propose an approach that provides a user with a guideline by suggesting undiscovered knowledge in the form of predicates. This approach firstly generates a set of candidate predicates by analyzing a pre-defined predicate by users. Second, it discards unqualified ones from the set of candidate predicates using a filtering method dealing with two criteria, uniqueness and support. The qualified candidate predicates are suggested, and selected by the user, and finally, his knowledge is enriched by merging the selected predicates with pre-defined ones.