Fast and reliable anomaly detection in categorical data

@inproceedings{Akoglu2012FastAR,
  title={Fast and reliable anomaly detection in categorical data},
  author={Leman Akoglu and Hanghang Tong and Jilles Vreeken and Christos Faloutsos},
  booktitle={CIKM},
  year={2012}
}
Spotting anomalies in large multi-dimensional databases is a crucial task with many applications in finance, health care, security, etc. We introduce COMPREX, a new approach for identifying anomalies using pattern-based compression. Informally, our method finds a collection of dictionaries that describe the norm of a database succinctly, and subsequently flags those points dissimilar to the norm---with high compression cost---as anomalies. Our approach exhibits four key features: 1) it is… CONTINUE READING
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