Name
Abstract | ||
|---|---|---|
Online monitoring user cardinalities in graph streams is fundamental for many applications such as anomaly detection. These graph streams may contain edge duplicates and have a large number of user-item pairs, which makes it infeasible to exactly compute user cardinalities due to limited computational and memory resources. Existing methods are designed to approximately estimate user cardinalities,... |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TKDE.2020.2975625 | IEEE Transactions on Knowledge and Data Engineering |
Keywords | DocType | Volume |
Estimation,Heuristic algorithms,Registers,Monitoring,Real-time systems,Anomaly detection,Memory management | Journal | 34 |
Issue | ISSN | Citations |
1 | 1041-4347 | 0 |
PageRank | References | Authors |
0.34 | 0 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peng Jia | 1 | 0 | 0.34 |
| Ping-Hui Wang | 2 | 236 | 33.39 |
| Yuchao Zhang | 3 | 0 | 0.34 |
| Xiangliang Zhang | 4 | 728 | 87.74 |
| Jing Tao | 5 | 64 | 16.92 |
| Jianwei Ding | 6 | 2 | 2.74 |
| Xiaohong Guan | 7 | 0 | 0.34 |
| Don Towsley | 8 | 0 | 0.34 |