A Personalized Collaborative Recommendation Algorithm Based on Hybrid Information

摘要

Personalized recommendation systems can help people to find interesting things and they are widely used with the development of electronic commerce. Many recommendation systems employ the collaborative filtering technology, which has been proved to be one of the most successful techniques in recommender systems in recent years. With the gradual increase of users and items in electronic commerce systems, the time consuming nearest neighbor collaborative filtering search of the target customer in the total user space resulted in the failure of ensuring the real time requirement of recommender system. The paper proposed a personalized recommendation algorithm using hybrid information. User and item information is used for collaborative filtering to produce the recommendations. The recommendation joining user information and item information collaborative filtering is more scalable than the traditional one.