Similarity issues in attribute implications from data with fuzzy attributes

Abstract

We study similarity in formal concept analysis of data tables with fuzzy attributes. We focus on similarity related to attribute implications, i.e. rules A rArr B describing dependencies "each object which has all attributes from A has also all attributes from B". We present several formulas for estimation of similarity of outputs in terms of similarity of inputs. The results answer some natural questions such as how much do truth degrees of A1 rArr B and A2 rArr B differ in terms of similarity of A1 to A2?