Mining opened frequent itemsets to generate maximal Boolean association rules

Abstract

Lots of association rules may be generated in the process of association rules minging. It leads to users hard to find important information they needed. The maximal Boolean association rules have the advantages that these rules contain a small number and don't lose the rules' information. Thereby it increased the efficiency of the users' analysis about the rules and saved the storage space. Opened frequent itemsets and closed frequent itemsets can be used to mine the maximal Boolean association rules. In this paper, we analyse the property of maximal Boolean association rules and propose an algorithm of mining opened frequent itemset. Finally, we verify this algorithm by an example.