| Can llm already serve as a database interface? a big bench for large-scale database grounded text-to-sqls J Li, B Hui, G Qu, J Yang, B Li, B Li, B Wang, B Qin, R Geng, N Huo, ... Advances in Neural Information Processing Systems 36, 2024 | 149 | 2024 |
| Efficient algorithms for densest subgraph discovery on large directed graphs C Ma, Y Fang, R Cheng, LVS Lakshmanan, W Zhang, X Lin Proceedings of the 2020 ACM SIGMOD International Conference on Management of …, 2020 | 75 | 2020 |
| Graphix-t5: Mixing pre-trained transformers with graph-aware layers for text-to-sql parsing J Li, B Hui, R Cheng, B Qin, C Ma, N Huo, F Huang, W Du, L Si, Y Li Proceedings of the AAAI Conference on Artificial Intelligence 37 (11), 13076 …, 2023 | 61 | 2023 |
| Linc: a motif counting algorithm for uncertain graphs C Ma, R Cheng, LVS Lakshmanan, T Grubenmann, Y Fang, X Li Proceedings of the VLDB Endowment 13 (2), 155-168, 2019 | 56 | 2019 |
| DeepTEA: effective and efficient online time-dependent trajectory outlier detection X Han, R Cheng, C Ma, T Grubenmann Proceedings of the VLDB Endowment 15 (7), 1493-1505, 2022 | 28 | 2022 |
| A convex-programming approach for efficient directed densest subgraph discovery C Ma, Y Fang, R Cheng, LVS Lakshmanan, X Han Proceedings of the 2022 International Conference on Management of Data, 845-859, 2022 | 22 | 2022 |
| On directed densest subgraph discovery C Ma, Y Fang, R Cheng, LVS Lakshmanan, W Zhang, X Lin ACM Transactions on Database Systems (TODS) 46 (4), 1-45, 2021 | 22 | 2021 |
| Effective community search over large star-schema heterogeneous information networks Y Jiang, Y Fang, C Ma, X Cao, C Li Proceedings of the VLDB Endowment 15 (11), 2307-2320, 2022 | 20 | 2022 |
| On analyzing graphs with motif-paths X Li, R Cheng, KCC Chang, C Shan, C Ma, H Cao Proceedings of the VLDB Endowment 14 (6), 1111-1123, 2021 | 20 | 2021 |
| Densest subgraph discovery on large graphs: applications, challenges, and techniques Y Fang, W Luo, C Ma Proceedings of the VLDB Endowment 15 (12), 3766-3769, 2022 | 18 | 2022 |
| Efficient directed densest subgraph discovery C Ma, Y Fang, R Cheng, LVS Lakshmanan, W Zhang, X Lin ACM SIGMOD Record 50 (1), 33-40, 2021 | 15 | 2021 |
| Finding locally densest subgraphs: a convex programming approach C Ma, R Cheng, LVS Lakshmanan, X Han Proceedings of the VLDB Endowment 15 (11), 2719-2732, 2022 | 14 | 2022 |
| Leveraging contextual graphs for stochastic weight completion in sparse road networks X Han, R Cheng, T Grubenmann, S Maniu, C Ma, X Li Proceedings of the 2022 SIAM International Conference on Data Mining (SDM …, 2022 | 9 | 2022 |
| Efficient and Effective Algorithms for Generalized Densest Subgraph Discovery Y Xu, C Ma, Y Fang, Z Bao Proceedings of the ACM on Management of Data 1 (2), 1-27, 2023 | 8 | 2023 |
| Motif paths: A new approach for analyzing higher-order semantics between graph nodes X Li, TN Chan, R Cheng, C Shan, C Ma, K Chang HKU Technique Reports 3, 4, 2019 | 7 | 2019 |
| A survey of densest subgraph discovery on large graphs W Luo, C Ma, Y Fang, LVS Lakshmanan arXiv preprint arXiv:2306.07927, 2023 | 6 | 2023 |
| Scalable algorithms for densest subgraph discovery W Luo, Z Tang, Y Fang, C Ma, X Zhou 2023 IEEE 39th International Conference on Data Engineering (ICDE), 287-300, 2023 | 6 | 2023 |
| On Querying Connected Components in Large Temporal Graphs H Xie, Y Fang, Y Xia, W Luo, C Ma Proceedings of the ACM on Management of Data 1 (2), 1-27, 2023 | 5 | 2023 |
| Accelerating directed densest subgraph queries with software and hardware approaches C Ma, Y Fang, R Cheng, LVS Lakshmanan, X Han, X Li The VLDB Journal 33 (1), 207-230, 2024 | 3 | 2024 |
| A Counting-based Approach for Efficient k-Clique Densest Subgraph Discovery Y Zhou, Q Guo, Y Fang, C Ma Proceedings of the ACM on Management of Data 2 (3), 1-27, 2024 | 2 | 2024 |
Reynold ChengACM Distinguished Member, HKU Computer Science Professor在 cs.hku.hk 的电子邮件经过验证
