E-Commerce Personalized Recommendation

Abstract

With the rapid development of electronic commerce, the problem of "information overload" leads to the difficulty that user can't search the required goods effectively , personalized recommendation technology has been applied in e-commerce and popularization. By using the method of qualitative analysis of the current e-commerce site, the paper compare the information retrieval, association rule, content-based filtering and collaborative filtering four main recommendation technologies and analysis the advantages and disadvantages in the application layer, the recommendation technologies are introduced to review e-commerce research hot topic in the field of personalized recommendation, and analysis the current domestic e-commerce personalized recommendation theory research and application status, finally propose the challenges faced by e-commerce personalized recommendation domain.