Research of the Personalized Recommender for E- Commerce Based on web usage mining and Collaborative Filtering Technique

摘要

Personalized recommender services of E-Commerce provides users with the preference items based on their lnterest.Through web log mining,Forms the users' access matrix,Calculate the similarity of users' browsing habits and get the k-nearest neighbor users,According to neighbors' project evaluation,forecast the target user's evaluation of the project and give A top-N recommended items. Experiments show that the algorithm efficiency are achieved satisfactory recommendation results and solve the problem of new users in a degree.