Abstract

The purchasing behavior of users on the internet can directly reflect the user's preferences and motivation. Retailers can grasp the shopping characteristics of buyers by analyzing the user behavior and sales performance is improved. An E-commerce website with behavior analysis features is designed based on the data mining algorithm of association rules. The different buying preferences can be found by analyzing the purchasing behaviors of users with different sexes. Further the personalized recommend for users with different sexes is realized.

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