Abstract: Collaborative filtering is widely accepted and applied currently as one of the most popular personalized recommendation methods. It is an implementation method based on content that has considerable advantages in accuracy. The core issue of collaborative filtering is how to work out the calculation of similarity. In this paper, we introduce the traditional collaborative filtering algorithm and make similarity calculation more accurately by optimizing the traditional formula of similarity. Experimental results show that the optimized algorithm can improve the accuracy of the recommendation and reduce the MAE (Mean Absolute Error, MAE) efficiently.

Key words: recommendation methods, similarity, collaborative filtering, MAE