Study of the Model of E-commerce Personalized Recommendation System Based on Data Mining

The integration of multiple recommendation algorithms using various data and the real-time requirement are pressing problems in the development of e-commerce personalized service. This paper introduces recommendation methods and the timing and manners of recommendation result display, presents multiple recommendation algorithms that reflect the latest achievements in data mining research, designs a model of the e-commerce personalized recommendation system based on data mining. In the model, the rule type library and the recommendation method library are employed and the libraries are designed independently for the recommendation rule types, the recommendation algorithms, the recommendation mode rules, the recommendation methods, effectively guaranteeing the real-time, efficient operation of multiple recommendation algorithms using various data, and the quality and efficiency of the personalized recommendation system.