The collaborative filtering based on co-ratings

Collaborative filtering is one of the most extensive and successful personalized recommendation algorithm in e-commerce recommendation system.Affected by data sparsity,the traditional collaborative filtering algorithms does not reflect the interest similarity of uses calculating similarity between users on the smaller set of common rated items accurately,seriously affecting the accuracy of recommendation system.To solve this problem,collaborative filtering algorithm based on co-ratings was proposed by analyzing the distribution of co-ratings and relationship between co-ratings and similarity,directly using co-ratings as a criterion to select nearest neighbor without calculating similarity.Experiments on MovieLens datasets show that the algorithm can make a substantial increase in prediction accuracy and recommendation coverage.