Counterfactual contextual bandit for recommendation under delayed feedback
Author:
Funder
National Key R &D Program of China
National Science Fund for Excellent Young Scholars
Natural Science Foundation of China
the major key project of PCL
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00521-024-09800-0.pdf
Reference67 articles.
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3. Zheng G, Zhang F, Zheng Z, Xiang Y, Yuan NJ, Xie X, Li Z (2018) Drn: A deep reinforcement learning framework for news recommendation. In: Proceedings of the 2018 World Wide Web Conference, 167–176. https://doi.org/10.1145/3178876.3185994
4. Shams S, Anderson D, Leith D (2021) Cluster-based bandits: Fast cold-start for recommender system new users. In: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval. https://doi.org/10.1145/3404835.3463033
5. Wu S, Wang Y, Jing Q, Dong D, Dou D, Yao Q (2023) Coldnas: Search to modulate for user cold-start recommendation. In: Proceedings of the ACM Web Conference 2023, pp. 1021–1031. https://doi.org/10.1145/3543507.3583344
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