| FRAUDAR: Bounding Graph Fraud in the Face of Camouflage B Hooi, HA Song, A Beutel, N Shah, K Shin, C Faloutsos Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge …, 2016 | 433 | 2016 |
| CoreScope: Graph Mining Using k-Core Analysis—Patterns, Anomalies and Algorithms K Shin, T Eliassi-Rad, C Faloutsos 2016 IEEE 16th International Conference on Data Mining (ICDM), 469-478, 2016 | 162 | 2016 |
| Midas: microcluster-based detector of anomalies in edge streams S Bhatia, B Hooi, M Yoon, K Shin, C Faloutsos Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3242-3249, 2020 | 126 | 2020 |
| M-zoom: Fast dense-block detection in tensors with quality guarantees K Shin, B Hooi, C Faloutsos Joint european conference on machine learning and knowledge discovery in …, 2016 | 116 | 2016 |
| Fast and Accurate Anomaly Detection in Dynamic Graphs with a Two-Pronged Approach M Yoon, B Hooi, K Shin, C Faloutsos Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 101 | 2019 |
| BEAR: Block Elimination Approach for Random Walk with Restart on Large Graphs K Shin, J Jung, S Lee, U Kang Proceedings of the 2015 ACM SIGMOD International Conference on Management of …, 2015 | 95 | 2015 |
| Graph-based fraud detection in the face of camouflage B Hooi, K Shin, HA Song, A Beutel, N Shah, C Faloutsos ACM Transactions on Knowledge Discovery from Data (TKDD) 11 (4), 1-26, 2017 | 94 | 2017 |
| How Much and When Do We Need Higher-order Information in Hypergraphs? A Case Study on Hyperedge Prediction S Yoon, H Song, K Shin, Y Yi Proceedings of The Web Conference 2020, 2627-2633, 2020 | 92 | 2020 |
| Fully Scalable Methods for Distributed Tensor Factorization K Shin, L Sael, U Kang IEEE Transactions on Knowledge and Data Engineering 29 (1), 100-113, 2017 | 92 | 2017 |
| Structural Patterns and Generative Models of Real-world Hypergraphs MT Do, S Yoon, B Hooi, K Shin Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 88 | 2020 |
| Patterns and anomalies in k-cores of real-world graphs with applications K Shin, T Eliassi-Rad, C Faloutsos Knowledge and Information Systems 54 (3), 677-710, 2018 | 86 | 2018 |
| DenseAlert: Incremental Dense-Subtensor Detection in Tensor Streams K Shin, B Hooi, J Kim, C Faloutsos Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge …, 2017 | 86 | 2017 |
| Hypergraph Motifs: Concepts, Algorithms, and Discoveries G Lee, J Ko, K Shin Proceedings of the VLDB Endowment 13 (11), 2256-2269, 2020 | 81 | 2020 |
| Distributed methods for high-dimensional and large-scale tensor factorization K Shin, U Kang 2014 IEEE International Conference on Data Mining, 989-994, 2014 | 81 | 2014 |
| D-Cube: Dense-Block Detection in Terabyte-Scale Tensors K Shin, B Hooi, J Kim, C Faloutsos Proceedings of the Tenth ACM International Conference on Web Search and Data …, 2017 | 79 | 2017 |
| How do hyperedges overlap in real-world hypergraphs?-patterns, measures, and generators G Lee, M Choe, K Shin Proceedings of the Web Conference 2021, 3396-3407, 2021 | 67 | 2021 |
| SWeG: Lossless and Lossy Summarization of Web-Scale Graphs K Shin, A Ghoting, M Kim, H Raghavan The World Wide Web Conference, 1679-1690, 2019 | 64 | 2019 |
| Incremental Lossless Graph Summarization J Ko, Y Kook, K Shin Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 58 | 2020 |
| 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 | 57 | 2020 |
| S-HOT: Scalable High-Order Tucker Decomposition J Oh, K Shin, EE Papalexakis, C Faloutsos, H Yu Proceedings of the Tenth ACM International Conference on Web Search and Data …, 2017 | 53 | 2017 |
Christos FaloutsosCMUVerified email at cs.cmu.edu
