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A User Interest Recommendation Based on Collaborative Filtering
2016
Proceedings of the 2016 2nd International Conference on Artificial Intelligence and Industrial Engineering (AIIE 2016)
unpublished
The traditional collaborative filtering algorithm cannot response user interest with time and is lack of time effectiveness. These problems lead to poor recommendation quality. On the basis of the neighbor-based collaborative filtering, a fused method of improved similarity and user interest is proposed. To begin with, we compute similarity from global perspectives obtained with Jaccard similarity, local perspectives obtained with Bhattacharyya Coefficient. Furthermore, we adopt the forgetting
doi:10.2991/aiie-16.2016.122
fatcat:jcs2fjijsjhylfwltrwxrwp4sq