An improved similarity algorithm based on Stability Degree for item-based collaborative filtering

With an exponentially growing amount of information being added to the Internet, finding efficient and valuable information is becoming more difficult. Collaborative Filtering acts a very important role in web service personalization and Recommender System. In this paper, Stability Degree was proposed to improve the accuracy of Item based collaboration filtering, three kinds of Stability Degree were introduced into similarity computation, and the results show that the prediction accuracy can be improved by 25 percents.