Fuzzy Attribute Implications: Computing Non-redundant Bases Using Maximal Independent Sets

Abstract. This note describes a method for computation of non-redundant bases of attribute implications from data tables with fuzzy attributes. Attribute implications are formulas describing particular dependencies of attributes in data. A non-redundant basis is a minimal set of attribute implications such that each attribute implication which is true in a given data (semantically) follows from the basis. Our bases are uniquely given by so-called systems of pseudo-intents. We reduce the problem of computing systems of pseudo-intents to the problem of computing maximal independent sets in certain graphs. We outline theoretical foundations, the algorithm, and present demonstrating examples.

• Type: Conference
• Year: 2005
• Where: AUSAI
• Authors: Radim Belohlávek, Vilém Vychodil
• Keywords: Artificial Intelligence, Attribute Implication, AUSAI 2005, Non-redundant Bases, Non-redundant Basis