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Exploring temporal effects for location recommendation on location-based social networks
Abstract
Location-based social networks (LBSNs) have attracted an inordinate number of users and greatly enriched the urban experience in recent years. The availability of spatial, temporal and social information in online LBSNs offers an unprecedented opportunity to study various aspects of human behavior, and enable a variety of location-based services such as location recommendation. Previous work studied spatial and social influences on location recommendation in LBSNs. Due to the strong correlations between a user's check-in time and the corresponding check-in location, recommender systems designed for location recommendation inevitably need to consider temporal effects. In this paper, we introduce a novel location recommendation framework, based on the temporal properties of user movement observed from a real-world LBSN dataset. The experimental results exhibit the significance of temporal patterns in explaining user behavior, and demonstrate their power to improve location recommendation performance.
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Cited by
GeoMF: joint geographical modeling and matrix factorization for point-of-interest recommendation
Lian, D., Zhao, C., Xie, X., Sun, G., Chen, E., & Rui, Y. (2014) · Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/2623330.2623638 · Cited by 608
Learning Graph-based POI Embedding for Location-based Recommendation
Xie, M., Yin, H., Wang, H., Xu, F., Chen, W., & Wang, S. (2016) · Proceedings of the 25th ACM International on Conference on Information and Knowledge Management · doi:10.1145/2983323.2983711 · Cited by 391
Where to Go Next: A Spatio-Temporal Gated Network for Next POI Recommendation
Zhao, P., Luo, A., Liu, Y., Xu, J., Li, Z., Zhuang, F., Sheng, V. S., & Zhou, X. (2022) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2020.3007194 · Cited by 357
Rank-GeoFM: A Ranking based Geographical Factorization Method for Point of Interest Recommendation
Li, X., Cong, G., Li, X.-L., Pham, T.-A. N., & Krishnaswamy, S. (2015) · Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval · doi:10.1145/2766462.2767722 · Cited by 340
Zhang, J.-D., & Chow, C.-Y. (2015) · Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval · doi:10.1145/2766462.2767711 · Cited by 288
Metadata
- Authors
- Gao, H., Tang, J., Hu, X., & Liu, H.
- Venue
- Proceedings of the 7th ACM conference on Recommender systems
- Publisher
- ACM
- Published
- 2013-10-12
- Pages
- 93-100
- OpenAlex
- W1984189333
- Cited by
- 513
- References
- 0
- FWCI
- 59.36
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Gao, H., Tang, J., Hu, X., & Liu, H. (2013). Exploring temporal effects for location recommendation on location-based social networks. Proceedings of the 7th ACM conference on Recommender systems. https://doi.org/10.1145/2507157.2507182
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