To solve the problem of efficiency bottleneck of Apriori-like algorithm, we propose a high-efficient association rule mining algorithm, namely EARM( Efficient Association Rule Mining) algorithm via further study of association rule mining and typical Apriori algorithm.General kinds of Apriori-like algorithm always produce huge number of candidate itemset, and it's a grave burden to mining efficiency. At the same time Apriori-like algorithm needs repeated confirming of the database FETCH in every stage circulation. That is also a great burden for the system. In addition, only use the threshold of support for measurement of the frequent items, but not really think that the actual trade amount and the consuming of different commodity will produce the different payoff and others; EARM algorithm make good improvement for this shortage, and perfect for the mining efficiency of the association rule, and apply in the CRM system well. This paper will research , analyze and verify in detail on EARM algorithm and it's application.In this paper, introduce the association rule , it's algorithm and it's history firstly, we can know that although the birth time is not long of the association rule, it's development and application in life is speedy. Secondly, introduce the theory and character of the Apriori-like algorithm, based on this, propose the efficient EARM algorithm. Then this paper analyze the theory , structure and application of the EARM algorithm at length , and compare the implement's efficiency of the EARM with the Apriori-like algorithm. Then give the application's realization of the EARM in Customer Relation Management system to make the theory upgrade practical application. |