Association Rules And Its Application In Selling

With the development of data mining, the commercial value of data mining attract more and more industry, they are eager to use data mining to create more value. The standard to measure whether a enterprises has create more value is the increase of sales volume. Association rules is one of data mining algorithms which are used widely.The application of association rules in merchandise sales although has success case early, but with the increasingly competition of business, how to improve the efficiency of the recommendation is a problem to solve eagerly.In order to solve the problem of how to improve the efficiency of the rec ommendation, in this thesis do some works like following:Firstly, deeply researched the technology of association rule and clustering algorithm is based on the large of literatures.And picked out the best fitted association rule and clustering algorithm for the recommendation through most of experiments.Secondly, use the clustering algorithm which is picked out to carry out th e characteristics of users and classified users by their characteristics.Change th e data set to vector dataset on base of the user classification.this change impr oved the efficiency of miningThen, use the association rule which is picked out to mining the vector d ataset which has been changed and carry out the result of mining which are ai med at users of different classifications. Based on the above ideas, this thesis proposes a CAM (Cluster-Association Mining) algorithm;Finally, the CAM algorithm is realized on the real data. The results show that, this algorithm is pertinence and effective.