APPLICATION RESEARCH FOR ASSOCIATION RULES MINING IN CLOTHING STORE

In the association rules mining field, it can be found interesting links between transaction records, which can help to make many business decisions. While it is difficult to find the links between transactions by the traditional manual methods as the Clothing store sales records are very complicated. Analyzing support and confidence of transaction, based on Aprior ialgorithm, it gets mining frequent itemsets and association rules. Through transaction compression, it can improve efficiency of the algorithm. Finally it gets the customer's buying habits and shopping tendencies, and can improve store management level, thus promote the development of the enterprise.