Two-step reduction of GOSCL based on subsets quality measure and stability index

Abstract

Generalized One-Sided Concept Lattices (GOSCL) represent a tool for extraction of hidden hierarchical structure among the datasets with different types of attributes. The specific problem of this method is an interpretation of the results from large created hierarchies, what often leads to the selection of the most relevant concepts. Subsets quality measure and stability index are techniques used for the ranking of the concepts relevance. In this paper we describe an approach which combines these two ranking techniques. The proposed approach is illustrated by an example and the experiments with the effect of reduction on generated input data tables are also provided.