| Title | Joint Modeling of Users' Interests and Mobility Patterns for Point-of-Interest Recommendation |
| Authors | Yin, Hongzhi Cui, Bin Huang, Zi Wang, Weiqing Wu, Xian Zhou, Xiaofang |
| Affiliation | Univ Queensland, Sch Informat Technol & Elect Engn, Brisbane, Qld 4072, Australia. Peking Univ, Sch EECS, Key Lab High Confidence Software Technol MOE, Haidian Qu, Beijing Shi, Peoples R China. Soochow Univ, Sch Comp Sci & Technol, Suzhou Shi, Jiangsu Sheng, Peoples R China. |
| Keywords | Recommender system Location-based service Probabilistic generative model Joint Modeling |
| Issue Date | 2015 |
| Publisher | ACM International Conference on Multimedia (MM) |
| Citation | ACM International Conference on Multimedia (MM).2015,819-822. |
| Abstract | Point-of-interest (POI) recommendation has become an important means to help people discover interesting places, especially when users travel out of town. However, extreme sparsity of user-POI matrix creates a severe challenge. To cope with this challenge, we propose a unified probabilistic generative model, Topic-Region. Model (TRM), to simultaneously discover the semantic, temporal and spatial patterns of users' check-in activities, and to model their joint effect on users' decision-making for POIs. We conduct extensive experiments to evaluate the performance of our TRM on two real large-scale datasets, and the experimental results clearly demonstrate that TRM outperforms the state-of-art methods. |
| URI | http://hdl.handle.net/20.500.11897/436570 |
| DOI | 10.1145/2733373.2806339 |
| Indexed | EI CPCI-S(ISTP) |
| Appears in Collections: | 信息科学技术学院 高可信软件技术教育部重点实验室 |
