Author:
Xu Shuai,Xu Jianqiu,Li Bohan,Fu Xiaoming
Publisher
Springer Nature Switzerland
Reference26 articles.
1. Chen, Y., Wang, X., Fan, M., Huang, J., Yang, S., Zhu, W.: Curriculum meta-learning for next poi recommendation. In: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 2692–2702 (2021)
2. Dang, W., et al.: Predicting human mobility via graph convolutional dual-attentive networks. In: Proceedings of the 15th ACM International Conference on Web Search and Data Mining, pp. 192–200 (2022)
3. Ding, J., Yu, G., Li, Y., Jin, D., Gao, H.: Learning from hometown and current city: cross-city poi recommendation via interest drift and transfer learning. In: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, vol. 3, no. 4, pp. 1–28 (2019)
4. Fan, Z., Arai, A., Song, X., Witayangkurn, A., Kanasugi, H., Shibasaki, R.: A collaborative filtering approach to citywide human mobility completion from sparse call records. In: Proceedings of the 25th International Joint Conference on Artificial Intelligence, pp. 2500–2506 (2016)
5. Feng, J., et al.: Deepmove: predicting human mobility with attentional recurrent networks. In: Proceedings of the 2018 World Wide Web Conference, pp. 1459–1468 (2018)