Name
Abstract | ||
|---|---|---|
Financial institutions are always interested in ensuring security and quality for their customers. Banks, for instance, need to identify and avoid harmful transactions. In order to detect fraudulent operations, data mining techniques based on customer profile generation and verification are commonly used. However, these approaches are not supported by Visual Analytics techniques yet. We propose a Visual Analytics approach for supporting and fine-tuning profile analysis and reducing false positive alarms. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.2312/eurp.20161138 | EuroVis (Posters) |
Field | DocType | Citations |
Data science,Time series,Profile analysis,Computer science,Visual analytics,Analytics | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Roger A. Leite | 1 | 19 | 4.67 |
| Theresia Gschwandtner | 2 | 171 | 17.43 |
| Silvia Miksch | 3 | 2212 | 174.85 |
| Erich Gstrein | 4 | 0 | 1.35 |
| Johannes Kuntner | 5 | 2 | 1.38 |