Abstract:

Recommender system is one of the key techniques in internet applications. The system analyzes user’s behavior, and recommends products initiative to replace the passive acceptance of user requests. The recommender system can improve not only the user experience but also the user’s desire to buy something. Collaborative filtering algorithm is widely used in the recommender system. In a largescale network, traditional collaborative filtering algorithms have extreme sparseness problem, and thus being inefficient. A collaborative filtering algorithm is proposed, which is designed by the largescale network segmentation rules. The algorithm uses the idea of divide and conquer algorithm, and decomposes problems into subproblems to solve, hence reaching the optimization of algorithm.

Key words: recommender system;similarity calculation;collaborative filtering;network segmentation