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Open Access
Issue
ITM Web Conf.
Volume 78, 2025
International Conference on Computer Science and Electronic Information Technology (CSEIT 2025)
Article Number 01034
Number of page(s) 13
Section Deep Learning and Reinforcement Learning – Theories and Applications
DOI https://doi.org/10.1051/itmconf/20257801034
Published online 08 September 2025
  1. Zhou, X., Chen, L., Zhang, Y., et al.: 'Deep reinforcement learning for recommender systems: A survey and new perspectives', arXiv:2004.13465, 2020 [Google Scholar]
  2. Yu, F., Zhu, Q., Wu, Y., et al.: 'Deep reinforcement learning for recommendation with explicit user-item interactions'. Proc. Int. Joint Conf. Neural Networks (IJCNN), 2020, pp. 1–8 [Google Scholar]
  3. Zhou, Y., Li, Y., Tan, V.Y.F.: 'Neural contextual bandits with UCB-based exploration'. Proc. AAAI Conf. Artificial Intelligence, 2020, 34, (04), pp. 6877–6884 [Google Scholar]
  4. Wang, H., Wu, Q., Wang, H.: 'Factorization bandits for interactive recommendation: Improvements and extensions', Information Sciences, 2021, 564, pp. 271–286 [Google Scholar]
  5. Zhang, W., Liu, Y., Li, Y.: 'Variational Thompson sampling with Gaussian processes'. Advances in Neural Information Processing Systems (NeurIPS), 2021, 34, pp. 21876–21888 [Google Scholar]
  6. Lin, C., Wang, Y.: 'Adaptive UCB with dynamic confidence adjustment for non-stationary environments', ACM Trans. Intelligent Systems and Technology, 2022, 13, (4), pp. 1–25 [Google Scholar]
  7. Fang, J., Wu, J., Chen, L.: 'Sliding-window Thompson sampling for drifting user preferences'. Proc. ACM Web Conference (WWW), 2023, pp. 3124–3133 [Google Scholar]
  8. Liu, X., Zhang, J., Wu, Y., et al.: 'Graph contextual bandits for recommendation'. Proc. ACM Web Conference (WWW), 2021, pp. 1080–1090 [Google Scholar]
  9. Wang, S., Zhang, Y., Liu, Q.: 'Transformer-based contextual bandits for sequential recommendation'. Proc. 16th ACM Conf. Recommender Systems (RecSys), 2022, pp. 292–301 [Google Scholar]
  10. Chen, H., Li, X., Wang, T.: 'Collaborative Thompson sampling with implicit feedback', ACM Trans. Recommender Systems, 2020, 4, (3), pp. 1–25 [Google Scholar]
  11. Huang, Z., Su, C., Li, S., et al.: 'Knowledge-aware contextual bandits for cross-domain recommendation', IEEE Trans. Knowledge and Data Engineering, 2022, 34, (10), pp. 4801–4814 [Google Scholar]
  12. Tang, R., Li, M., Zhao, Y.: 'Beyond regret: Multi-objective evaluation for bandit-based recommender systems', Information Processing & Management, 2023, 60, (2), 103198 [Google Scholar]

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