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Article

Unsupervised Graph Anomaly Detection Algorithms Implemented in Apache Spark

Lobachevskii Journal of Mathematics. 2018. Vol. 39. No. 9. P. 1262-1269.
Semenov A., Mazeev A., Dmitry D., Timur Y.

The graph anomaly detection problem occurs in many application areas and can be solved by spotting outliers in unstructured collections of multi-dimensional data points, which can be obtained by graph analysis algorithms. We implement the algorithm for the small community analysis and the approximate LOF algorithm based on Locality-Sensitive Hashing, apply the algorithms to a real world graph and evaluate scalability of the algorithms. We use Apache Spark as one of the most popular Big Data frameworks.