Abstract
The paper presents a general method of imposing constraints in formal concept analysis of tabular data with fuzzy attributes. The constraints represent a user-defined requirements which are supplied along with the input data table. The main effect is to filter-out conceptual clusters (outputs of the analysis) which are not compatible with the constraint, in a computationally efficient way. Our approach covers several examples studied before, e.g. crisply generated concepts and constraints by hedges. Keywords— formal concept analysis, fuzzy attribute, tabular data, constraint, fuzzy closure operator, fuzzy concept lattice
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