Research on Adaptive Recommendation Algorithm in Personalized E-Supermarket Service System

摘要

To meet the personalized needs of customers in E-supermarket, a new adaptive recommendation algorithm based on support vector machine was proposed in the paper. First, user profile was organized hierarchically into field information and atomic information needs, considering similar information needs in the group users. Support vector machine (SVM) was adopted for collaborative recommendation in classification mode, and then Vector Space Model (VSM) was used for content-based recommendation according to atomic information needs. The algorithm had overcome the demerit of using collaborative or content-based recommendation solely, which improved the precision and recall in a large degree. It also fits for large scale group recommendation.