The application of web log in collaborative filtering recommendation algorithm

Collaborative filtering algorithm has been widely used in the electronic commerce recommendation system in recent years, but collaborative filtering algorithm also has some problems, such as data sparseness and lack of individuation, these problems affected the efficiency and accuracy of recommendation algorithm. According to the problems, this paper proposes the method of Web log analysis and user clustering related technology, this method transform implicit interest to explicit interest of user for commodities, it not only solves the problem sparse data also improve the recommend of accuracy.