Mining Constraint Association Rule Using Direct Algorithm

Abstract

Discovering association rules has received considerable research attention and several fast algorithms for mining association rules have been developed. In practice, users are often interested in a subset of association rules. For example, they may only want rules that contain a specific item or categories.Constraints can be applied to the association rule mining and integrating them into the mining algorithm can dramatically reduce the execution time. This paper presents constraints as boolean expressions over the presence or absence of items which are integrated into the association rule algorithm. To generate constraint association rule, Direct algorithm is used in this system. Constraint association rule is applied for Mini Market Transaction Dataset. The process of discovering association rules at single level has received significant research attention and several algorithms for mining frequent itemsets have been developed. The discovery of multi-level association rules is very much useful in many applications. In this system, multi-level constraint association rule by Direct algorithm is presented.