An efficient method to factorize fuzzy attribute-oriented concept lattices

Factorization by similarity is a mathematical technique used in formal concept analysis with fuzzy attributes for reducing the complexity of different types of fuzzy concept lattices. In this paper we find the structure of the factor lattice of a fuzzy attribute-oriented concept lattice, namely the intervals representing the blocks of this lattice. We provide a procedure for generating the infimum and the supremum concepts of these intervals as fixpoints of a fuzzy closure operator. This theoretical result allows to develop a more efficient algorithm for building the factor lattice of the fuzzy attribute-oriented concept lattice. A comparison between our approach and the existing algorithms is presented.