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The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

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Research Article | Open Access |

Anomaly Detection with Machine Learning and Graph Databases in Fraud Management

Author 1: Shamil Magomedov Author 2: Sergei Pavelyev Author 3: Irina Ivanova Author 4: Alexey Dobrotvorsky Author 5: Marina Khrestina Author 6: Timur Yusubaliev
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 9, No. 11 · Published 2018 · Cited by 15

DOI: https://doi.org/10.14569/IJACSA.2018.091104

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Abstract

In this paper, the task of fraud detection using the methods of data analysis and machine learning based on social and transaction graphs is considered. The algorithms for feature calculation, outlier detection and identifying specific sub-graph patterns are proposed. Software realization of the proposed algorithms is described and the results of experimental study of the algorithms on the sets of real and synthetic data are presented.

Keywords

Data analysis machine learning graph database fraud detection anti-money laundering

How to Cite this Article

Magomedov, S., Pavelyev, S., Ivanova, I., Dobrotvorsky, A., Khrestina, M., & Yusubaliev, T. (2018). Anomaly Detection with Machine Learning and Graph Databases in Fraud Management. International Journal of Advanced Computer Science and Applications, 9(11). https://doi.org/10.14569/IJACSA.2018.091104

Magomedov, Shamil, et al.. "Anomaly Detection with Machine Learning and Graph Databases in Fraud Management." International Journal of Advanced Computer Science and Applications, vol. 9, no. 11, 2018, https://doi.org/10.14569/IJACSA.2018.091104.

@article{Magomedov2018,
  title     = {Anomaly Detection with Machine Learning and Graph Databases in Fraud Management},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {9},
  number    = {11},
  year      = {2018},
  publisher = {The Science and Information Organization},
  author    = {Shamil Magomedov and Sergei Pavelyev and Irina Ivanova and Alexey Dobrotvorsky and Marina Khrestina and Timur Yusubaliev},
  doi       = {10.14569/IJACSA.2018.091104},
  url       = {https://doi.org/10.14569/IJACSA.2018.091104}
}

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