| Fairness-aware tensor-based recommendation Z Zhu, X Hu, J Caverlee Proceedings of the 27th ACM international conference on information and …, 2018 | 196 | 2018 |
| 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 | 161 | 2021 |
| 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 | 125 | 2020 |
| 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 | 124 | 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 | 113 | 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 | 92 | 2020 |
| 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 | 90 | 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 | 74 | 2021 |
| Improving top-k recommendation via jointcollaborative autoencoders Z Zhu, J Wang, J Caverlee The World Wide Web Conference, 3483-3482, 2019 | 63 | 2019 |
| 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 | 56 | 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 | 43 | 2022 |
| 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 | 43 | 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 | 37 | 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 | 35 | 2020 |
| 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 | 24 | 2021 |
| 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 | 23 | 2022 |
| 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 | 23 | 2020 |
| Breaking the trilemma of privacy, utility, and efficiency via controllable machine unlearning Z Liu, G Dou, E Chien, C Zhang, Y Tian, Z Zhu Proceedings of the ACM Web Conference 2024, 1260-1271, 2024 | 21 | 2024 |
| 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 | 20 | 2022 |
| Global Voices, local biases: Socio-cultural prejudices across languages A Mukherjee, C Raj, Z Zhu, A Anastasopoulos arXiv preprint arXiv:2310.17586, 2023 | 13 | 2023 |
James CaverleeProfessor, Computer Science and Engineering, Texas A&M UniversityPreverjeni e-poštni naslov na cse.tamu.edu