Collaborative Filtering Meets Mobile Recommendation: A User-Centered Approach
Vincent W. Zheng, Bin Cao, Yu Zheng, Xing Xie and Qiang Yang ( AAAI-10 ) http://www.aaai.org/ocs/index.php/AAAI/AAAI10/paper/viewFile/1615/1964 The paper “Collaborative Filtering Meets Mobile Recommendation: A User-Centered Approach” introduces an approach, user-centered collaborative location and activity filtering (UCLAF), to extract data from many users and apply collaborative filtering to find like-minded users and like-patterned activities at different locations. These findings from social information can help to do mobile recommendation on location and activities. Different from previous work, Vincent et al. model the user-location activity relations with a tensor representation; and suggest that a regularized tensor and matrix decomposition are better to address the sparse data problem. The result of this paper shows that UCLAF has a better performance compared to some state-of-the-art solutions. With the rapidly increase of internet data about location, location tracking...