Session-aware recommender system using double deep reinforcement learning
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Networks and Communications,Hardware and Architecture,Information Systems,Software
Link
https://link.springer.com/content/pdf/10.1007/s10844-023-00824-x.pdf
Reference47 articles.
1. Aggarwal, C. C. (2016). Content-Based Recommender Systems. Recommender Systems: The Textbook (pp. 139–166). Cham: Springer International Publishing.
2. Bedi, P., Khurana, P., & Sharma, R. (2021). Session based recommendations using CNN-LSTM with fuzzy time series. In International conference on artificial intelligence and speech technology (pp. 432–446). https://doi.org/10.1007/978-3-030-95711-7_36
3. Cai, Q., Zhao, & Hu, H. (2018). Session-aware music recommendation via a generative model approach. Soft Computing, 22, 1023–1031. https://doi.org/10.1007/s00500-016-2407-4
4. Chen, H. (2021). A DQN-based Recommender system for item-list recommendation. In IEEE International conference on big data (big data) (pp. 5699–5702). https://doi.org/10.1109/BigData52589.2021.9671947
5. Chen, W., Ren, P., & Cai, F., et al. (2020). Improving end-to-end sequential recommendations with intent-aware diversication. In Proceedings of the 29th ACM international conference on information & knowledge management (pp. 175–184). https://doi.org/10.1145/3340531.3411897
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