| Explainable recommendation: A survey and new perspectives Y Zhang, X Chen Foundations and Trends® in Information Retrieval 14 (1), 1-101, 2020 | 667 | 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 | 429 | 2018 |
| Learning heterogeneous knowledge base embeddings for explainable recommendation Q Ai, V Azizi, X Chen, Y Zhang Algorithms 11 (9), 137, 2018 | 359* | 2018 |
| 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 | 316 | 2018 |
| Joint representation learning for top-n recommendation with heterogeneous information sources Y Zhang, Q Ai, X Chen, WB Croft Proceedings of the 2017 ACM on Conference on Information and Knowledge …, 2017 | 284 | 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 | 214* | 2019 |
| Aesthetic-based clothing recommendation W Yu, H Zhang, X He, X Chen, L Xiong, Z Qin Proceedings of the 2018 world wide web conference, 649-658, 2018 | 199 | 2018 |
| Recbole: Towards a unified, comprehensive and efficient framework for recommendation algorithms WX Zhao, S Mu, Y Hou, Z Lin, Y Chen, X Pan, K Li, Y Lu, H Wang, C Tian, ... Proceedings of the 30th ACM International Conference on Information …, 2021 | 159* | 2021 |
| 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 | 147 | 2016 |
| Dynamic explainable recommendation based on neural attentive models X Chen, Y Zhang, Z Qin Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 53-60, 2019 | 113 | 2019 |
| Learning a hierarchical embedding model for personalized product search Q Ai, Y Zhang, K Bi, X Chen, WB Croft Proceedings of the 40th International ACM SIGIR Conference on Research and …, 2017 | 111 | 2017 |
| Personalized key frame recommendation X Chen, Y Zhang, Q Ai, H Xu, J Yan, Z Qin Proceedings of the 40th international ACM SIGIR conference on research and …, 2017 | 105 | 2017 |
| Bridge text and knowledge by learning multi-prototype entity mention embedding Y Cao, L Huang, H Ji, X Chen, J Li Association for Computational Linguistics, 2017 | 100 | 2017 |
| Counterfactual data-augmented sequential recommendation Z Wang, J Zhang, H Xu, X Chen, Y Zhang, WX Zhao, JR Wen Proceedings of the 44th international ACM SIGIR conference on research and …, 2021 | 65 | 2021 |
| CAFE: Coarse-to-fine neural symbolic reasoning for explainable recommendation Y Xian, Z Fu, H Zhao, Y Ge, X Chen, Q Huang, S Geng, Z Qin, G De Melo, ... Proceedings of the 29th ACM International Conference on Information …, 2020 | 61 | 2020 |
| Time matters: Sequential recommendation with complex temporal information W Ye, S Wang, X Chen, X Wang, Z Qin, D Yin Proceedings of the 43rd international ACM SIGIR conference on research and …, 2020 | 61 | 2020 |
| Counterfactual explainable recommendation J Tan, S Xu, Y Ge, Y Li, X Chen, Y Zhang Proceedings of the 30th ACM International Conference on Information …, 2021 | 55 | 2021 |
| Generate natural language explanations for recommendation H Chen, X Chen, S Shi, Y Zhang arXiv preprint arXiv:2101.03392, 2021 | 48 | 2021 |
| Adversarial distillation for efficient recommendation with external knowledge X Chen, Y Zhang, H Xu, Z Qin, H Zha ACM Transactions on Information Systems (TOIS) 37 (1), 1-28, 2018 | 38 | 2018 |
| Causal collaborative filtering S Xu, Y Ge, Y Li, Z Fu, X Chen, Y Zhang arXiv preprint arXiv:2102.01868, 2021 | 32 | 2021 |
Yongfeng ZhangRutgers University, Computer ScienceVerified email at rutgers.edu
