A Collaborative Filtering Recommendation Algorithm Based on Improved Bhattacharyya Coefficient

• 1、Tianjin University Department of Management and Economics，Tianjin 300072

Abstract：Neighbor-based collaborative filtering recommendation is a very common recommendation method in current recommendation system information filtering technology. However, the traditional neighbor based collaborative filtering recommendation method have to rely entirely on the common scoring items of users, and the accuracy of prediction in extremely sparse data sets is not high. Bhattacharyya coefficient for collaborative filtering can effectively improve the above problems. But there are two obvious drawbacks to this approach: one is that it fails to consider the case that the number of scoring items of two users is not the same; and the other is thatA Collaborative Filtering Recommendation Algorithm Based on Improved Bhattacharyya Coefficient there is no specific cA Collaborative Filtering Recommendation Algorithm Based on Improved Bhattacharyya Coefficientonsideration for user preferences. In this paper, the Bhattacharyya coefficient collaborative filtering algorithm is improved to make full use of all users\' scoring information. In addition, considering users\' positive scoring preferences for projects, the final user similarity value is calculated by using projects with user scores higher than their own average scores. The experimental results show that the algorithm obtains better recommendation results on the dataset and improves the accuracy of the recommendation.

Keywords： Collaborative filtering Bhattacharyya coefficient for collaborative filtering Similarity measure