Scalable computation of the extensional and intensional stability of formal concepts

The effective use of the concept lattice in large datasets has been always limited by the large volume of extracted knowledge. The stability measure has been shown to be of valuable help for knowledge selection. In this paper, we introduce the SC-MG algorithm to efficiently compute both types of stability, i.e. extensional and intensional. The guiding idea is to exploit the relationship between stability and minimal generators in order to compute both measures. The performed experiments show the efficiency of the SC-MG algorithm. In addition, it sharply outperforms the pioneering approaches of the literature.