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Boolean Algebraic Algorithm for Mining Association Rules from Large Database

S. Sumathi, R. Lawrance


In the earlier days, the association rule mining is used for Market Basket analysis to find the regularity in purchasing behavior of customer. Association Rule Mining (ARM) is one of the functionalities in Data Mining, to find the relationships among the items in a particular set of itemsets. There are huge numbers of algorithms to find relationships among the items. In this paper we introduce a new Boolean algebraic algorithm for finding frequent itemsets and deriving the association rules in a large transaction database. It has two phases. In the first phase, it finds the frequent itemsets. In the second phase, by using the Boolean AND and XOR operator, it derives the association rules from the founded frequent itemset in first phase. This algorithm mines the association rules efficiently than Apriori.


Association Rule Mining, Boolean Algebra, Data Mining, Frequent Item Set Mining.

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