Empowering Next POI Recommendation with Multi-Relational Modeling-Reference-Cited by-同舟云学术

Empowering Next POI Recommendation with Multi-Relational Modeling

Published:2022-07-06 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Author:

Huang Zheng¹,Ma Jing¹,Dong Yushun¹,Foutz Natasha Zhang¹,Li Jundong¹

Affiliation:

1. University of Virginia, Charlottesville, VA, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3477495.3531801

Reference28 articles.

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2. The influence of temporal and spatial features on the performance of next-place prediction algorithms

3. Feng , J. , Li , Y. , Zhang , C. , Sun , F. , Meng , F. , Guo , A. , and Jin , D . Deepmove: Predicting human mobility with attentional recurrent networks . In WWW ( 2018 ), pp. 1459 -- 1468 . Feng, J., Li, Y., Zhang, C., Sun, F., Meng, F., Guo, A., and Jin, D. Deepmove: Predicting human mobility with attentional recurrent networks. In WWW (2018), pp. 1459--1468.

4. Next place prediction using mobility Markov chains

5. Hamilton , W. L. , Ying , R. , and Leskovec , J . Inductive representation learning on large graphs . In NIPS ( 2017 ), pp. 1025 -- 1035 . Hamilton, W. L., Ying, R., and Leskovec, J. Inductive representation learning on large graphs. In NIPS (2017), pp. 1025--1035.

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