Formal Concept Analysis Based Association Rules Extraction
Generating a huge number of association rules
reduces their utility in the decision making
process, done by domain experts. 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 and
its relevance which is related to the confidence
of rule. 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.
Keywords: Association rules, formal concept analysis, quality measure
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