Dynamic and evolving fuzzy concept lattices

Abstract

Fuzzy formal concept analysis enables us to add structure to data by identifying coherent groups of related objects and attributes. In a situation where data is added dynamically, the concept lattice may evolve in different ways - either in content (more objects added to existing concepts) or in structure (entirely new concepts are created). This change can be monitored and quantified by means of a recently defined distance metric. In this paper, we present a new and more efficient algorithm for calculating the fuzzy distance between concept lattices, and illustrate the evolution of concept lattices by simple examples.