| Next-item recommendation with sequential hypergraphs J Wang, K Ding, L Hong, H Liu, J Caverlee Proceedings of the 43rd international ACM SIGIR conference on research and …, 2020 | 255 | 2020 |
| Be more with less: Hypergraph attention networks for inductive text classification K Ding, J Wang, J Li, D Li, H Liu arXiv preprint arXiv:2011.00387, 2020 | 225 | 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 | 140 | 2021 |
| Graph prototypical networks for few-shot learning on attributed networks K Ding, J Wang, J Li, K Shu, C Liu, H Liu Proceedings of the 29th ACM International Conference on Information …, 2020 | 139 | 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 | 112 | 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 | 96 | 2021 |
| Improving top-k recommendation via jointcollaborative autoencoders Z Zhu, J Wang, J Caverlee The World Wide Web Conference, 3483-3482, 2019 | 62 | 2019 |
| Item relationship graph neural networks for e-commerce W Liu, Y Zhang, J Wang, Y He, J Caverlee, PPK Chan, DS Yeung, ... IEEE Transactions on Neural Networks and Learning Systems 33 (9), 4785-4799, 2021 | 53 | 2021 |
| Sequential recommendation for cold-start users with meta transitional learning J Wang, K Ding, J Caverlee Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021 | 49 | 2021 |
| Time to Shop for Valentine's Day: Shopping Occasions and Sequential Recommendation in E-commerce J Wang, R Louca, D Hu, C Cellier, J Caverlee, L Hong Proceedings of the 13th International Conference on Web Search and Data …, 2020 | 40 | 2020 |
| Meta propagation networks for graph few-shot semi-supervised learning K Ding, J Wang, J Caverlee, H Liu Proceedings of the AAAI conference on artificial intelligence 36 (6), 6524-6531, 2022 | 37 | 2022 |
| 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 | 36 | 2022 |
| A hierarchical self-attentive model for recommending user-generated item lists Y He, J Wang, W Niu, J Caverlee Proceedings of the 28th ACM international conference on information and …, 2019 | 36 | 2019 |
| Recurrent recommendation with local coherence J Wang, J Caverlee Proceedings of the Twelfth ACM International Conference on Web Search and …, 2019 | 33 | 2019 |
| Learning strong graph neural networks with weak information Y Liu, K Ding, J Wang, V Lee, H Liu, S Pan Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 30 | 2023 |
| 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 | 30 | 2020 |
| Mamba4rec: Towards efficient sequential recommendation with selective state space models C Liu, J Lin, J Wang, H Liu, J Caverlee arXiv preprint arXiv:2403.03900, 2024 | 25 | 2024 |
| Adaptive hierarchical translation-based sequential recommendation Y Zhang, Y He, J Wang, J Caverlee Proceedings of the Web Conference 2020, 2984-2990, 2020 | 16 | 2020 |
| Learning to augment for casual user recommendation J Wang, Y Le, B Chang, Y Wang, EH Chi, M Chen Proceedings of the ACM Web Conference 2022, 2183-2194, 2022 | 12 | 2022 |
| Exploring heterogeneous metadata for video recommendation with two-tower model J Wang, A Yessenalina, A Roshan-Ghias arXiv preprint arXiv:2109.11059, 2021 | 12 | 2021 |
