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Incremental Stream Clustering for Anomaly Detection and Classification
Anders Holst, Jan Ekman
100 - 107
10.3233/978-1-60750-754-3-100
Frontiers in Artificial Intelligence and Applications
Volume 227: Eleventh Scandinavian Conference on Artificial Intelligence
Abstract

We have designed a framework for Bayesian Statistical Anomaly Detection, called ISC, or Incremental Stream Clustering. It learns the normal situation incrementally, and can on the fly detect anomalous cases. When this happens, a new cluster can be created, so similar cases can be detected in the future. In this way, the framework performs incremental clustering, while at the same time either classifying a new case as belonging to one of the known clusters or indicating that it is from a previously unseen situation.

$35.00 / €27.50 / £22.00
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