Interpretation of Fuzzy Attribute Subsets in Generalized One-Sided Concept Lattices

Abstract

In this paper we describe possible interpretation and reduction of fuzzy attributes in GeneralizedOne-sided Concept Lattices (GOSCL). This type of concept lattices represent generalization ofFormal Concept Analysis (FCA) suitable for analysis of datatables with different types of attributes. FCA as well as generalized one-sided concept lattices represent conceptual data miningmethods. With growing number of attributes the interpretation of fuzzy subsets may become unclear, hence another interpretation of this fuzzy attribute subsets can be valuable. The originalityof the presented method is based on the usage of one-sided concept lattices derived from submodels of former object-attribute model by grouping attributes with the same truth value structure.This leads to new method for attribute reduction in GOSCL environment.