| Heterogeneous graph attention network X Wang, H Ji, C Shi, B Wang, P Cui, YY Yu, P WWW 2019, 2019 | 2151 | 2019 |
| Heterogeneous graph attention networks for semi-supervised short text classification H Linmei, T Yang, C Shi, H Ji, X Li EMNLP 2019, 2019 | 356 | 2019 |
| Interpreting and Unifying Graph Neural Networks with An Optimization Framework M Zhu, X Wang, C Shi, H Ji, P Cui WWW 2021, 2021 | 156 | 2021 |
| HGAT: Heterogeneous graph attention networks for semi-supervised short text classification T Yang, L Hu, C Shi, H Ji, X Li, L Nie ACM TOIS 2021, 2021 | 119 | 2021 |
| Heterogeneous Graph Propagation Network H Ji, X Wang, C Shi, B Wang, P Yu IEEE TKDE, 2021 | 57 | 2021 |
| Who You Would Like to Share With? A Study of Share Recommendation in Social E-commerce H Ji, J Zhu, X Wang, C Shi, B Wang, X Tan, Y Li, S He AAAI 2021, 2021 | 38 | 2021 |
| Gated graph neural attention networks for abstractive summarization Z Liang, J Du, Y Shao, H Ji Neurocomputing 2021, 2021 | 27 | 2021 |
| Heterogeneous Graph Neural Network for Recommendation J Shi, H Ji, C Shi, X Wang, Z Zhang, J Zhou ICML Workshop, 2020 | 20 | 2020 |
| Attention based meta path fusion for heterogeneous information network embedding H Ji, C Shi, B Wang PRICAI 2018, 2018 | 18 | 2018 |
| Large-scale Comb-K Recommendation H Ji, J Zhu, C Shi, X Wang, B Wang, C Zhang, Z Zhu, F Zhang, Y Li WWW 2021, 2021 | 11 | 2021 |
| Heterogeneous graph neural network with distance encoding H Ji, C Yang, C Shi, P Li ICDM 2021, 2021 | 9 | 2021 |
| From abstract to details: A generative multimodal fusion framework for recommendation F Xiao, L Deng, J Chen, H Ji, X Yang, Z Ding, B Long Proceedings of the 30th ACM International Conference on Multimedia, 258-267, 2022 | 5 | 2022 |
| Distance Information Improves Heterogeneous Graph Neural Networks C Shi, H Ji, Z Lu, Y Tang, P Li, C Yang IEEE Transactions on Knowledge and Data Engineering, 2023 | | 2023 |
