A threshold free implication rule mining

Abstract

Typically, before association rules are mined, a user needs to determine a support threshold in order to obtain only the frequent item sets. Having users to determine a support threshold attracts a number of issues. We propose an association rule mining framework that does not require a pre-set support threshold. The framework is developed based on implication of propositional logic. The experiments show that our approach is able to identify meaningful association rules within an acceptable execution time.