Estimations of Similarity in Formal Concept Analysis of Data with Graded Attributes

We study similarity in formal concept analysis of data tables with graded attributes. We focus on similarity related to formal concepts and concept lattices, i.e. the outputs of formal concept analysis. We present several formulas for estimation of similarity of outputs in terms of similarity of inputs. The results answer some problems which arose in previous investigation as well as some natural questions concerning similarity in conceptual data analysis. The derived formulas enable us to compute an estimation of similarity of concept lattices much faster than one can compute their exact similarity. We omit proofs due to lack of space.