An Information-Theoretic Approach to Detecting Changes in Multi-Dimensional Data Streams

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Summary

This paper uses relative entropy, also called the Kullback-Leibler distance, to measure the difference between two given distributions, which generalizes Kulldorff’s spatial scan statistic, allowing us to quantitatively identify specific regions in space where large changes have occurred.

Type
article
Published
2006-01-01
Cited by
261
References
34

Keywords

STREAMS, Computer science, Data mining, Data stream mining

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