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Discovery of Frequent Episodes in Event Sequences

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Abstract

Sequences of events describing the behavior and actions of users or systems can be collected in several domains. An episode is a collection of events that occur relatively close to each other in a given partial order. We consider the problem of discovering frequently occurring episodes in a sequence. Once such episodes are known, one can produce rules for describing or predicting the behavior of the sequence. We give efficient algorithms for the discovery of all frequent episodes from a given class of episodes, and present detailed experimental results. The methods are in use in telecommunication alarm management.

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Authors and Affiliations

  1. Department of Computer Science, University of Helsinki, P.O. Box 26, FIN-00014, Finland

    Heikki Mannila, Hannu Toivonen & A. Inkeri Verkamo

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  1. Heikki Mannila
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  2. Hannu Toivonen
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  3. A. Inkeri Verkamo
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Mannila, H., Toivonen, H. & Inkeri Verkamo, A. Discovery of Frequent Episodes in Event Sequences. Data Mining and Knowledge Discovery 1, 259–289 (1997). https://doi.org/10.1023/A:1009748302351

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