Case-based reasoning
Discovery of fraud rules for telecommunications—challenges and solutions
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Machine Learning
Expert Systems with Applications: An International Journal
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Fraud in mobile telecommunications is a complex and dynamic problem for Telecom operators. These companies have developed and are exploring new ways of making the fraud detection process more efficient. Most of these attempts are based in fraud management systems, capable of detecting fraudulent communications. In this paper, we present a case-based reasoning system that aids fraud analysts in the classification of potential fraud cases. The system developed, presents to the analyst the most similar past cases, representing suspicious communication episodes that were previously investigated. We also describe an example of how the system is used.