| Explicit factor models for explainable recommendation based on phrase-level sentiment analysis Y Zhang, G Lai, M Zhang, Y Zhang, Y Liu, S Ma Proceedings of the 37th international ACM SIGIR conference on Research …, 2014 | 852 | 2014 |
| Explainable recommendation: A survey and new perspectives Y Zhang, X Chen Foundations and Trends® in Information Retrieval 14 (1), 1-101, 2020 | 820 | 2020 |
| Sequential recommendation with user memory networks X Chen, H Xu, Y Zhang, J Tang, Y Cao, Z Qin, H Zha Proceedings of the eleventh ACM international conference on web search and …, 2018 | 481 | 2018 |
| Learning heterogeneous knowledge base embeddings for explainable recommendation Q Ai, V Azizi, X Chen, Y Zhang Algorithms 11 (9), 137, 2018 | 440* | 2018 |
| Reinforcement knowledge graph reasoning for explainable recommendation Y Xian, Z Fu, S Muthukrishnan, G De Melo, Y Zhang Proceedings of the 42nd international ACM SIGIR conference on research and …, 2019 | 411 | 2019 |
| Towards conversational search and recommendation: System ask, user respond Y Zhang, X Chen, Q Ai, L Yang, WB Croft Proceedings of the 27th acm international conference on information and …, 2018 | 365 | 2018 |
| Clip-adapter: Better vision-language models with feature adapters P Gao, S Geng, R Zhang, T Ma, R Fang, Y Zhang, H Li, Y Qiao International Journal of Computer Vision, 1-15, 2023 | 315 | 2023 |
| Joint Representation Learning for Top-N Recommendation with Heterogeneous Information Sources Y Zhang, Q Ai, X Chen, WB Croft The 26th ACM International Conference on Information and Knowledge Management, 2017 | 305 | 2017 |
| Personalized fashion recommendation with visual explanations based on multimodal attention network: Towards visually explainable recommendation X Chen, H Chen, H Xu, Y Zhang, Y Cao, Z Qin, H Zha Proceedings of the 42nd International ACM SIGIR Conference on Research and …, 2019 | 259* | 2019 |
| BERT with history answer embedding for conversational question answering C Qu, L Yang, M Qiu, WB Croft, Y Zhang, M Iyyer Proceedings of the 42nd international ACM SIGIR conference on research and …, 2019 | 210 | 2019 |
| Fairness-aware explainable recommendation over knowledge graphs Z Fu, Y Xian, R Gao, J Zhao, Q Huang, Y Ge, S Xu, S Geng, C Shah, ... Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020 | 174 | 2020 |
| Fairness-Aware Group Recommendation with Pareto Efficiency X Lin, M Zhang, Y Zhang, Z Gu, Y Liu, S Ma Proceedings of the 11th ACM Conference on Recommender Systems, 2017 | 173 | 2017 |
| Detecting stress based on social interactions in social networks H Lin, J Jia, J Qiu, Y Zhang, G Shen, L Xie, J Tang, L Feng, TS Chua IEEE Transactions on Knowledge and Data Engineering 29 (9), 1820-1833, 2017 | 160 | 2017 |
| Learning to rank features for recommendation over multiple categories X Chen, Z Qin, Y Zhang, T Xu Proceedings of the 39th International ACM SIGIR conference on Research and …, 2016 | 160 | 2016 |
| Relational collaborative filtering: Modeling multiple item relations for recommendation X Xin, X He, Y Zhang, Y Zhang, J Jose Proceedings of the 42nd international ACM SIGIR conference on research and …, 2019 | 155 | 2019 |
| Response ranking with deep matching networks and external knowledge in information-seeking conversation systems L Yang, M Qiu, C Qu, J Guo, Y Zhang, WB Croft, J Huang, H Chen The 41st international acm sigir conference on research & development in …, 2018 | 152 | 2018 |
| User-oriented fairness in recommendation Y Li, H Chen, Z Fu, Y Ge, Y Zhang Proceedings of the Web Conference 2021, 624-632, 2021 | 151 | 2021 |
| Towards Long-term Fairness in Recommendation Y Ge, S Liu, R Gao, Y Xian, Y Li, X Zhao, C Pei, F Sun, J Ge, W Ou, ... Proceedings of the 14th ACM International Conference on Web Search and Data …, 2021 | 151 | 2021 |
| Efficient neural matrix factorization without sampling for recommendation C Chen, M Zhang, Y Zhang, Y Liu, S Ma ACM Transactions on Information Systems (TOIS) 38 (2), 1-28, 2020 | 149 | 2020 |
| Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5) S Geng, S Liu, Z Fu, Y Ge, Y Zhang Proceedings of the 16th ACM Conference on Recommender Systems, 2022 | 132 | 2022 |
Xu Chen 陈 旭Associate Professor (pre-tenure), Renmin University of ChinaEmail confirmado em ruc.edu.cn
