The Analysis And Optimization Of Association Rules Algorithm In Data Mining

How to find the frequent itemsets from the given database efficiently is the most important issue of the association rule mining. As the main method of data mining, the research of the association rules has always been concerned. In the process of frequent itemsets discovery, how to improve the shortcomings of the Apriori algorithm has been the most popular study.Through analysis and research on Apriori algorithm and rough set theory, this paper put forward an improved method of Apriori algorithm. Firstly, this method reduced the number of the attributes in transaction database by the attribute reduction, then used the improved algorithm to generate association rules. The experiments showed that the improved algorithm improved the execution performance. Finally, this paper applied the improved method to mining the associated rules from the credit card customer information, in order to obtain the valuable knowledge on the development of the credit card business.