| Hierarchical Reinforcement Learning for Course Recommendation in MOOCs J Zhang, B Hao, B Chen, C Li, H Chen, J Sun Proceedings of the AAAI conference on artificial intelligence 33 (01), 435-442, 2019 | 198 | 2019 |
| Pre-training Graph Neural Networks for Cold-start Users and Items Representation B Hao, J Zhang, H Yin, C Li, H Chen The 14th ACM International WSDM Conference (WSDM'21), 2020 | 107 | 2020 |
| A Multi-strategy-based Pre-training Method for Cold-start Recommendation B Hao, H Yin, J Zhang, C Li, H Chen ACM Transactions on Information Systems 41 (2), 1-24, 2023 | 18 | 2023 |
| Motif-based Prompt Learning for Universal Cross-domain Recommendation B Hao, C Yang, L Guo, J Yu, H Yin The 17th ACM International Conference on Web Search and Data Mining, 2023 | 4 | 2023 |
| Self‐supervised Graph Learning for Occasional Group Recommendation B Hao, H Yin, C Li, H Chen International Journal of Intelligent Systems 37 (12), 10880-10902, 2022 | 4 | 2022 |
| Few-shot Representation learning for Cold-start users and items B Hao, J Zhang, C Li, H Chen Web and Big Data: 4th International Joint Conference, APWeb-WAIM 2020 …, 2020 | 4 | 2020 |
| Recommending Courses in MOOCs for Jobs: An Auto Weak Supervision Approach B Hao, J Zhang, C Li, H Chen, H Yin Machine Learning and Knowledge Discovery in Databases: Applied Data Science …, 2021 | 3 | 2021 |
| Instruction Tuning Large Language Models with Multi-modal Recommendation Instruction B Hao, Y Liu, L Li, J Wang, Y Peng Journal of Beijing University of Posts and Telecommunications, 2024, 2024 | | 2024 |
Hong ChenProfessor of computer science, Renmin University of China在 ruc.edu.cn 的电子邮件经过验证
