Abstract
One of the approaches applied in data analysis is related to the theory of concept lattices, also known as Formal Concept Analysis (FCA), which is suitable for processing and analysis of object-attribute input data models. Concept lattice represents hierarchically organized structure of clusters of objects (concepts) based on the presence of their shared attributes. While basic FCA framework works only with binary input data tables, several approaches were introduced in order to process fuzzy attributes. The model of Generalized One-Sided Concept Lattices (GOSCL) is suitable to work with different types of attributes used in input data tables, which helped in understanding and interpretation of analysis. One of the main issues which remains is large number of concepts for visualization to user. The solution is to provide user with the reduction methods and advanced dynamic visualization of concept lattices and their reductions. In this paper we introduce and compare some of the implemented visualizations and reductions applied to concept lattices generated from input data.
Published Version
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