Research On Dynamic Association Rule Mining Based On Grey Model

This paper proposed a dynamic meta-rule association rule mining algorithm based on Grey-cycle extension model.and a method of tendency mining based on Grey Markov model in dynamic association rule by combining the grey system theory,the dynamic association meta-rule mining and tendency mining together on the basis of the relevant knowledge.By setting up different models in view of different types of data,the given two algorithms fully take advantages of grey model when the original data is small and have a better effect for data modeling and prediction.And by applying the proposed methods in actual mining,they are proved to be valid and have higher prediction.By comparing the proposed methods with the traditional dynamic association meta-rule mining methods and tendency mining algorithm,the two methods are proved can min higher quality and stronger rules.And to a certain degree they overcome the blindness of mining and can maximum min effective and potential rules to effectively improve the efficiency of the dynamic association rule mining and reference value of the results.And different with the traditional algorithm,the proposed methods can get the rules with the change over time by analyzing the tendency of the rule through the mathematical models.