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Details for article 7 of 10 found articles
| Title: |
Employing Kullback-Leibler divergence and Latent Dirichlet Allocation for fraud detection in telecommunications |
| Author: |
Olszewski, Dominik |
| Appeared in: |
Intelligent data analysis |
| Paging: | Volume 16 (2012) nr. 3 pages 467-485 |
| Year: |
2012-05-09 |
| Contents: |
In this paper, a method for telecommunications fraud detection is proposed. The method is based on the user profiling using the Latent Dirichlet Allocation (LDA). Fraudulent behavior is detected with use of a threshold-type classification algorithm, allocating the telecommunication accounts into one of two classes: fraudulent account and non-fraudulent account. The paper provides also a method for automatic threshold computation. The accounts are classified with use of the Kullback-Leibler divergence (KL-divergence). Therefore, we also introduce three methods for approximating the KL-divergence between two LDAs. Finally, the results of experimental study on KL-divergence approximation and fraud detection in telecommunications are reported. |
| Publisher: |
IOS Press |
| Source file: |
Elektronische Wetenschappelijke Tijdschriften |
Details for article 7 of 10 found articles
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