Abstract
In this paper, we propose an efficient algorithm for anomaly detection from call data records. Anomalous users are detected based on fuzzy attribute values derived from their communication patterns. A clustering based algorithm is proposed to generate explanations to assist human analysts in validating the results.
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Nithi, Dey, L. (2009). Anomaly Detection from Call Data Records. In: Chaudhury, S., Mitra, S., Murthy, C.A., Sastry, P.S., Pal, S.K. (eds) Pattern Recognition and Machine Intelligence. PReMI 2009. Lecture Notes in Computer Science, vol 5909. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11164-8_38
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DOI: https://doi.org/10.1007/978-3-642-11164-8_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-11163-1
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