Loading...
Please wait, while we are loading the content...
Similar Documents
Chapter 1 Fraud Detection-Dense Subgraph Detection
| Content Provider | Semantic Scholar |
|---|---|
| Author | Zhao, Tong |
| Copyright Year | 2018 |
| Abstract | Fraud behaviors can be spotted everywhere on online applications such as social networks where the behavior data can be represented as large bipartite graphs. These graphs consist of links between followers and followees. Fraudulent actions such as fake followers usually result with creating large and dense subgraphs. For example, as a large number of follower buyers buy followers from one major follower seller, these follower buyers togethor with the bot followers controled by the seller will form a subgraph with high density. Hence many existing detection methods [15, 27, 25] estimate the suspiciousness of users by identifying whether they are within a dense subgraph. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://www3.nd.edu/~kogge/courses/cse60742-Fall2018/Public/StudentWork/KernelPaperv1/DSD_TZ.pdf |
| Alternate Webpage(s) | https://www3.nd.edu/~kogge/courses/cse60742-Fall2018/Public/StudentWork/KernelPaper-v2/DSD_TZ.pdf |
| Alternate Webpage(s) | https://www3.nd.edu/~kogge/courses/cse60742-Fall2018/Public/StudentWork/KernelPaperFinal/DSD_TZ.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
