Semantic approach for association rules extraction based on Formal Concept Analysis

The huge number of generated association rules limits the growth of more appropriate techniques to assist the decision maker. In this context, based on the theory of Formal Concept Analysis, we propose to extend the notion of Formal Concept through the generalization of the notion of itemset in order to consider the itemset as an intent, its support as the cardinality of the extent. Accordingly, we propose a new approach to extract interesting itemsets through the concept coverage. This approach uses a new quality-criteria of a rule: the relevance bringing a semantic added value to formal concept analysis approach to discover association rules.