Incremental Concept Formation made More Efficient by the Use of Associative Concepts

Formal Concept Analysis (FCA) is interested in the formation of concept lattices from binary relations between objects and attributes, a.k.a. contexts. Many algorithms have been proposed to generate the set of all concepts, and also the edges of the lattice between these concepts. We develop the principle and the code of a new algorithm combining two existing ones, Godin's and Bordat's algorithms. Then, we show by both a theoretical and practical study that it is the most efficient algorithm for sparse contexts, which are usually found in real applications.