| SSumM: Sparse Summarization of Massive Graphs K Lee, H Jo, J Ko, S Lim, K Shin Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 30 | 2020 |
| Dpgs: Degree-preserving graph summarization H Zhou, S Liu, K Lee, K Shin, H Shen, X Cheng Proceedings of the 2021 SIAM International Conference on Data Mining (SDM …, 2021 | 8 | 2021 |
| Monstor: an inductive approach for estimating and maximizing influence over unseen networks J Ko, K Lee, K Shin, N Park 2020 IEEE/ACM International Conference on Advances in Social Networks …, 2020 | 8* | 2020 |
| Slugger: lossless hierarchical summarization of massive graphs K Lee, J Ko, K Shin 2022 IEEE 38th International Conference on Data Engineering (ICDE), 472-484, 2022 | 5 | 2022 |
| Effective training strategies for deep-learning-based precipitation nowcasting and estimation J Ko, K Lee, H Hwang, SG Oh, SW Son, K Shin Computers & Geosciences 161, 105072, 2022 | 5 | 2022 |
| Personalized graph summarization: formulation, scalable algorithms, and applications S Kang, K Lee, K Shin 2022 IEEE 38th International Conference on Data Engineering (ICDE), 2319-2332, 2022 | 2 | 2022 |
| Deep-Learning-Based Precipitation Nowcasting with Ground Weather Station Data and Radar Data J Ko, K Lee, H Hwang, K Shin arXiv preprint arXiv:2210.12853, 2022 | 1 | 2022 |
| Are Edge Weights in Summary Graphs Useful?-A Comparative Study S Kang, K Lee, K Shin Advances in Knowledge Discovery and Data Mining: 26th Pacific-Asia …, 2022 | 1 | 2022 |
Kijung ShinAssistant Professor, KAISTVerified email at kaist.ac.kr
