Optimization of Association Rules Mining Apriori Algorithm Based on ACO

Discovering association rules between items in a large database of sales transactions has been described as an important database mining problem. Relationships between data are called associations. Association rule mining reveals such interesting relationships. These association rules are presented in a compact form, eliminating redundancy. Elimination of redundancy in the association rule set generated from large item is a challenging task. We show that the quality of rule sets from the Apriori algorithm for association rule mining can be improved by using Ant Colony Optimization (ACO). For this comparison we do a benchmark test using Abalone dataset from UCI machine learning repository.