Interactive recommender system via knowledge graph-enhanced reinforcement learning S Zhou, X Dai, H Chen, W Zhang, K Ren, R Tang, X He, Y Yu Proceedings of the 43rd international ACM SIGIR conference on research and …, 2020 | 161 | 2020 |
Large-scale interactive recommendation with tree-structured policy gradient H Chen, X Dai, H Cai, W Zhang, X Wang, R Tang, Y Zhang, Y Yu Proceedings of the AAAI conference on artificial intelligence 33 (01), 3312-3320, 2019 | 155 | 2019 |
Deep reinforcement learning based recommendation with explicit user-item interactions modeling F Liu, R Tang, X Li, W Zhang, Y Ye, H Chen, H Guo, Y Zhang arXiv preprint arXiv:1810.12027, 2018 | 149 | 2018 |
State representation modeling for deep reinforcement learning based recommendation F Liu, R Tang, X Li, W Zhang, Y Ye, H Chen, H Guo, Y Zhang, X He Knowledge-Based Systems 205, 106170, 2020 | 61 | 2020 |
Neural link prediction over aligned networks X Cao, H Chen, X Wang, W Zhang, Y Yu Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 23 | 2018 |
Intent preference decoupling for user representation on online recommender system Z Liu, H Chen, F Sun, X Xie, J Gao, B Ding, Y Shen Proceedings of the Twenty-Ninth International Conference on International …, 2021 | 19 | 2021 |
Studying the impact of data disclosure mechanism in recommender systems via simulation Z Chen, F Sun, Y Tang, H Chen, J Gao, B Ding ACM Transactions on Information Systems 41 (3), 1-26, 2023 | 8 | 2023 |
Proactively control privacy in recommender systems Z Chen, F Sun, Y Tang, H Chen, J Gao, B Ding arXiv preprint arXiv:2204.00279, 2022 | 5 | 2022 |
Large-scale interactive recommendation with tree-structured reinforcement learning H Chen, C Zhu, R Tang, W Zhang, X He, Y Yu IEEE Transactions on Knowledge and Data Engineering 35 (4), 4018-4032, 2021 | 3 | 2021 |
PURE: An Uncertainty-aware Recommendation Framework for Maximizing Expected Posterior Utility of Platform H Chen, Z Liu, C Xu, Z Chen, J Gao, B Ding | | |