The Study on the Application of Data Mining Based on Association Rules

Abstract

Association rule mining finds interesting association or correlation relationships among a large set of data items, which is an important task of data mining. Meanwhile, Apriori is an influential algorithm for mining frequent itemsets for Boolean association rules. Firstly, the concept and the effect of association rules are introduced and the classic algorithms of association rule are analyzed. In Apriori algorithm, most time is consumed for scanning the database repeatedly. Therefore, the methods are presented about improving the Apriori algorithm efficiency, which reduces a lot of time of scanning database and shortens the computation time of the algorithm. Furthermore, several typical applications of association rules in Market-Basket Analysis are given.