Analysis and Comparative of E-Commerce Personalized Recommendation

Yan Zhang

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 compares the information retrieval, association rule, content-based filtering and collaborative filtering, four main recommendation technologies, and analyses 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 analyses the current domestic e-commerce personalized recommendation theory research and application status, finally proposes the challenges faced by e-commerce personalized recommendation domain.