Comparable research of two collaborative filtering recommendation algorisms
Zhou Hai-pin · Journal of Guiyang University · 2015
The appearance of Web2. 0 has caused a geometric progression growth of the data of Internet. How to find the needed content in the vast information is a challenging problem,information recommendation system is appearing in order to solve this problem,and collaborative filtering algorithm is one of the most widely used algorithm. In this paper,we introduced two collaborative filtering recommendation algorisms: user based collaborative filtering algorism and item based collaborative filtering algorism,and made a comparison of the performance of the two algorisms by the film data of Movielens system. The results show that user based collaborative filtering algorism acts better in films recommendation.