| An experimental study of state-of-the-art entity alignment approaches X Zhao, W Zeng, J Tang, W Wang, FM Suchanek IEEE Transactions on Knowledge and Data Engineering 34 (6), 2610-2625, 2020 | 102 | 2020 |
| Collective entity alignment via adaptive features W Zeng, X Zhao, J Tang, X Lin 2020 IEEE 36th international conference on data engineering (ICDE), 1870-1873, 2020 | 97 | 2020 |
| Degree-aware alignment for entities in tail W Zeng, X Zhao, W Wang, J Tang, Z Tan Proceedings of the 43rd international ACM SIGIR conference on research and …, 2020 | 61 | 2020 |
| Reinforcement learning–based collective entity alignment with adaptive features W Zeng, X Zhao, J Tang, X Lin, P Groth ACM Transactions on Information Systems (TOIS) 39 (3), 1-31, 2021 | 46 | 2021 |
| Multi-modal entity alignment in hyperbolic space H Guo, J Tang, W Zeng, X Zhao, L Liu Neurocomputing 461, 598-607, 2021 | 40 | 2021 |
| Knowledge graph embedding by relational and entity rotation X Huang, J Tang, Z Tan, W Zeng, J Wang, X Zhao Knowledge-Based Systems 229, 107310, 2021 | 35 | 2021 |
| Towards entity alignment in the open world: An unsupervised approach W Zeng, X Zhao, J Tang, X Li, M Luo, Q Zheng Database Systems for Advanced Applications: 26th International Conference …, 2021 | 22 | 2021 |
| On entity alignment at scale W Zeng, X Zhao, X Li, J Tang, W Wang The VLDB Journal 31 (5), 1009-1033, 2022 | 21 | 2022 |
| Reinforced active entity alignment W Zeng, X Zhao, J Tang, C Fan Proceedings of the 30th ACM international conference on information …, 2021 | 20 | 2021 |
| Iterative Entity Alignment with Improved Neural Attribute Embedding. N Pang, W Zeng, J Tang, Z Tan, X Zhao DL4KG@ ESWC, 41-46, 2019 | 20 | 2019 |
| Entity linking via symmetrical attention-based neural network and entity structural features S Hu, Z Tan, W Zeng, B Ge, W Xiao Symmetry 11 (4), 453, 2019 | 20 | 2019 |
| Entity linking on Chinese microblogs via deep neural network W Zeng, J Tang, X Zhao IEEE Access 6, 25908-25920, 2018 | 20 | 2018 |
| Collective list-only entity linking: A graph-based approach W Zeng, X Zhao, J Tang, H Shang IEEE Access 6, 16035-16045, 2018 | 11 | 2018 |
| Toward entity alignment in the open world: an unsupervised approach with confidence modeling X Zhao, W Zeng, J Tang, X Li, M Luo, Q Zheng Data Science and Engineering 7 (1), 16-29, 2022 | 10 | 2022 |
| Measuring entity relatedness via entity and text joint embedding W Zeng, J Tang, X Zhao Neural Processing Letters 50, 1861-1875, 2019 | 9 | 2019 |
| Efficient and accurate traffic flow prediction via incremental tensor completion J Liao, J Tang, W Zeng, X Zhao IEEE Access 6, 36897-36905, 2018 | 9 | 2018 |
| Domain relation extraction from noisy Chinese texts N Pang, Z Tan, X Zhao, W Zeng, W Xiao Neurocomputing 418, 21-35, 2020 | 7 | 2020 |
| Matching knowledge graphs in entity embedding spaces: an experimental study W Zeng, X Zhao, Z Tan, J Tang, X Cheng IEEE Transactions on Knowledge and Data Engineering, 2023 | 6 | 2023 |
| To hop or not, that is the question: Towards effective multi-hop reasoning over knowledge graphs J Liao, X Zhao, J Tang, W Zeng, Z Tan World Wide Web 24 (5), 1837-1856, 2021 | 6 | 2021 |
| MOOPer: a large-scale dataset of practice-oriented online learning K Liu, X Zhao, J Tang, W Zeng, J Liao, F Tian, Q Zheng, J Huang, A Dai Knowledge Graph and Semantic Computing: Knowledge Graph Empowers New …, 2021 | 6 | 2021 |
Xiang ZhaoProfessor, National University of Defense Technology, ChinaVerified email at nudt.edu.cn
