Exploration in commercial websites on the association rules base on the consumers´ behavior

Association rules data mining on consumers condition in commercial websites is an important aspect of research in FP-Growth algorithm. In the general application of FP-Growth algorithm, the transaction data contain only the customers´ purchase acts data, and neglect the data of acts which contain customers browsing, selecting, evaluation, this phenomenon may lead to data distortion. For this reason, this text proposed a method which divides the customer acts data into browsing, evaluation, selection and purchasing four act data, and combines these data to the goods data, thus it can provides to commerce web site managers the results that more close to actual acts of the relevant rules.