Adaptive Graph Representation Learning for Next POI Recommendation-Reference-Cited by-同舟云学术

Adaptive Graph Representation Learning for Next POI Recommendation

Published:2023-07-18 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Author:

Wang Zhaobo¹^ORCID,Zhu Yanmin¹^ORCID,Wang Chunyang¹^ORCID,Ma Wenze¹^ORCID,Li Bo²^ORCID,Yu Jiadi¹^ORCID

Affiliation:

1. Shanghai Jiao Tong University, Shanghai, China

2. Hong Kong University of Science and Technology, Hong Kong, Hong Kong

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3539618.3591634

Reference40 articles.

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3. Yu Chen , Lingfei Wu , and Mohammed Zaki . 2020 . Iterative deep graph learning for graph neural networks: Better and robust node embeddings . NeurIPS , 19314--19326. Yu Chen, Lingfei Wu, and Mohammed Zaki. 2020. Iterative deep graph learning for graph neural networks: Better and robust node embeddings. NeurIPS, 19314--19326.

4. Chen Cheng Haiqin Yang Michael R Lyu and Irwin King. 2013. Where you like to go next: Successive point-of-interest recommendation. In IJCAI. 2605--2611. Chen Cheng Haiqin Yang Michael R Lyu and Irwin King. 2013. Where you like to go next: Successive point-of-interest recommendation. In IJCAI. 2605--2611.

5. Luca Franceschi Mathias Niepert Massimiliano Pontil and Xiao He. 2019. Learning discrete structures for graph neural networks. In ICML. 1972--1982. Luca Franceschi Mathias Niepert Massimiliano Pontil and Xiao He. 2019. Learning discrete structures for graph neural networks. In ICML. 1972--1982.

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