Next POI Recommendation Method Based on Category Preference and Attention Mechanism in LBSNs-Reference-Cited by-同舟云学术

Next POI Recommendation Method Based on Category Preference and Attention Mechanism in LBSNs

Published:2023 Issue: Volume: Page:12-19
ISSN:0302-9743
Container-title:Web and Big Data
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Author:

Wang Xueying,Liu Yanheng,Zhou Xu^ORCID,Leng Zhaoqi,Wang Xican

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-25198-6_2

Reference14 articles.

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3. Huang, L., Ma, Y., Wang, S., Liu, Y.: An attention-based spatiotemporal LSTM network for next POI recommendation. IEEE Trans. Serv. Comput. 14(6), 1585–1597 (2021)

4. Jiao, W., Fan, H., Midtbø, T.: A grid-based approach for measuring similarities of taxi trajectories. Sensors 20(11), 3118 (2020)

5. Liu, Q., Wu, S., Wang, L., Tan, T.: Predicting the next location: a recurrent model with spatial and temporal contexts. In: Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, February 12–17, 2016, Phoenix, Arizona, USA, pp. 194–200. AAAI Press (2016)

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1. Enhancing Spatio-temporal Semantics with Contrastive Learning for Next POI Recommendation;Lecture Notes in Computer Science;2024

2. PAPR:Periodic Aware Spatial temporal Network for POI Recommendation;2023 19th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD);2023-07-29