Point-of-interest Recommendation using Deep Semantic Model

Author:

Wang ZiweiORCID,Zeng JunORCID,Wen Junhao,Gao MinORCID,Zhou Wei

Funder

National Natural Science Foundation of China

Natural Science Foundation of Chongqing Municipality

Fundamental Research Funds for the Central Universities

Natural Science Foundation Project of Chongqing

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference39 articles.

1. Cheng, C., Yang, H., Lyu, M. R., & King, I. (2013). Where you like to go next: Successive point-of-interest recommendation. In Proceedings of the twenty-third international joint conference on artificial intelligence (pp. 2605–2611).

2. Cho, E., Myers, S. A., & Leskovec, J. (2011). Friendship and mobility: User movement in location-based social networks. In Proceedings of the 17th ACM SIGKDD international conference on knowledge discovery and data mining (pp. 1082–1090).

3. Choi, D.-W., Pei, J., & Heinis, T. (2017). Efficient mining of regional movement patterns in semantic trajectories. In Proceedings of the VLDB endowment, vol. 10, no. 13 (pp. 2073–2084).

4. Devlin, J., Chang, M., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In Proceedings of the 2019 conference of the north american chapter of the association for computational linguistics: human language technologies (pp. 4171–4186).

5. Gulcehre, C., Cho, K., Pascanu, R., & Bengio, Y. (2014). Learned-norm pooling for deep feedforward and recurrent neural networks. In Proceedings of the 2014th European conference on machine learning and knowledge discovery (pp. 530–546).

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