Real-time POI recommendation via modeling long- and short-term user preferences

Author:

Liu Xin,Yang Yongjian,Xu Yuanbo,Yang Funing,Huang Qiuyang,Wang Hong

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference30 articles.

1. An interactive multi-task learning framework for next POI recommendation with uncertain check-ins;Zhang;Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI,2020

2. Shanshan Feng, Lucas Vinh Tran, Gao Cong, Lisi Chen, Jing Li, and Fan Li. HME: A hyperbolic metric embedding approach for next-poi recommendation. In Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, SIGIR 2020, Virtual Event, China, July 25-30, 2020, pp. 1429–1438, 2020.

3. Qinyong Wang, Hongzhi Yin, Tong Chen, Zi Huang, Hao Wang, Yanchang Zhao, and Nguyen Quoc Viet Hung. Next point-of-interest recommendation on resource-constrained mobile devices. In WWW ’20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, pp. 906–916, 2020.

4. Ranzhen Li, Yanyan Shen, Yanmin Zhu. Next point-of-interest recommendation with temporal and multi-level context attention. In IEEE International Conference on Data Mining, ICDM 2018, Singapore, November 17–20, 2018, pp. 1110–1115, 2018.

5. Jing He, Xin Li, Lejian Liao, Dandan Song, and William K. Cheung. Inferring a personalized next point-of-interest recommendation model with latent behavior patterns. In Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, February 12-17, 2016, Phoenix, Arizona, USA, pp. 137–143, 2016.

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