| Fairness-aware tensor-based recommendation Z Zhu, X Hu, J Caverlee Proceedings of the 27th ACM international conference on information and …, 2018 | 152 | 2018 |
| Infusing disease knowledge into BERT for health question answering, medical inference and disease name recognition Y He, Z Zhu, Y Zhang, Q Chen, J Caverlee arXiv preprint arXiv:2010.03746, 2020 | 95 | 2020 |
| Popularity-opportunity bias in collaborative filtering Z Zhu, Y He, X Zhao, Y Zhang, J Wang, J Caverlee Proceedings of the 14th ACM International Conference on Web Search and Data …, 2021 | 91 | 2021 |
| Measuring and mitigating item under-recommendation bias in personalized ranking systems Z Zhu, J Wang, J Caverlee Proceedings of the 43rd international ACM SIGIR conference on research and …, 2020 | 84 | 2020 |
| Session-based recommendation with hypergraph attention networks J Wang, K Ding, Z Zhu, J Caverlee Proceedings of the 2021 SIAM International Conference on Data Mining (SDM …, 2021 | 60 | 2021 |
| Recommendation for new users and new items via randomized training and mixture-of-experts transformation Z Zhu, S Sefati, P Saadatpanah, J Caverlee Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020 | 55 | 2020 |
| Improving top-k recommendation via jointcollaborative autoencoders Z Zhu, J Wang, J Caverlee The World Wide Web Conference, 3483-3482, 2019 | 52 | 2019 |
| Popularity bias in dynamic recommendation Z Zhu, Y He, X Zhao, J Caverlee Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 49 | 2021 |
| Fairness among new items in cold start recommender systems Z Zhu, J Kim, T Nguyen, A Fenton, J Caverlee Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021 | 36 | 2021 |
| Unbiased implicit recommendation and propensity estimation via combinational joint learning Z Zhu, Y He, Y Zhang, J Caverlee Proceedings of the 14th ACM Conference on Recommender Systems, 551-556, 2020 | 36 | 2020 |
| Content-collaborative disentanglement representation learning for enhanced recommendation Y Zhang, Z Zhu, Y He, J Caverlee Proceedings of the 14th ACM Conference on Recommender Systems, 43-52, 2020 | 32 | 2020 |
| Modeling and detecting student attention and interest level using wearable computers Z Zhu, S Ober, R Jafari 2017 IEEE 14th international conference on wearable and implantable body …, 2017 | 30 | 2017 |
| Key opinion leaders in recommendation systems: Opinion elicitation and diffusion J Wang, K Ding, Z Zhu, Y Zhang, J Caverlee Proceedings of the 13th international conference on web search and data …, 2020 | 23 | 2020 |
| Quantifying and mitigating popularity bias in conversational recommender systems A Lin, J Wang, Z Zhu, J Caverlee Proceedings of the 31st ACM International Conference on Information …, 2022 | 22 | 2022 |
| Rabbit holes and taste distortion: Distribution-aware recommendation with evolving interests X Zhao, Z Zhu, J Caverlee Proceedings of the Web Conference 2021, 888-899, 2021 | 15 | 2021 |
| Improving the estimation of tail ratings in recommender system with multi-latent representations X Zhao, Z Zhu, Y Zhang, J Caverlee Proceedings of the 13th International Conference on Web Search and Data …, 2020 | 15 | 2020 |
| Fighting mainstream bias in recommender systems via local fine tuning Z Zhu, J Caverlee Proceedings of the Fifteenth ACM International Conference on Web Search and …, 2022 | 11 | 2022 |
| End-to-end learning for fair ranking systems J Kotary, F Fioretto, P Van Hentenryck, Z Zhu Proceedings of the ACM Web Conference 2022, 3520-3530, 2022 | 9 | 2022 |
| Fairness-aware recommendation of information curators Z Zhu, J Wang, Y Zhang, J Caverlee arXiv preprint arXiv:1809.03040, 2018 | 8 | 2018 |
| Addressing the target customer distortion problem in recommender systems X Zhao, Z Zhu, M Alfifi, J Caverlee Proceedings of The Web Conference 2020, 2969-2975, 2020 | 7 | 2020 |
James CaverleeProfessor, Computer Science and Engineering, Texas A&M UniversityVerified email at cse.tamu.edu
