Reduction of Concepts from Generalized One-Sided Concept Lattice Based on Subsets Quality Measure

Authors: Peter Butka, Jozef Pócs, Jana Pócsová
Year: 2015
Venue: Advances in Intelligent Systems and Computing Volume 314, Springer, 101-111
Product of the Action: No

One of the conceptual methods in data mining area is based on the onesided concept lattices, which belongs to approaches known as Formal ConceptAnalysis (FCA). It provides an analysis of objects clusters according to the set of fuzzy attributes. The specific problem of such approaches is sometimes large number of concepts created by the method, which can be crucial for the interpretation of the results and their usage in practice. In this chapter we describe the method for evaluation of concepts from generalized one-sided concept lattice based on the quality measure of objects subsets. Consequently, this method is able to select most relevant concepts according to their quality, which can lead to useful reduction of information from concept lattice. The usage of this approach is described by the illustrative example.