Data Mining and Knowledge Discovery

, Volume 1, Issue 3, pp 259–289

Discovery of Frequent Episodes in Event Sequences

Authors

  • Heikki Mannila
    • Department of Computer ScienceUniversity of Helsinki
  • Hannu Toivonen
    • Department of Computer ScienceUniversity of Helsinki
  • A. Inkeri Verkamo
    • Department of Computer ScienceUniversity of Helsinki
Article

DOI: 10.1023/A:1009748302351

Cite this article as:
Mannila, H., Toivonen, H. & Inkeri Verkamo, A. Data Mining and Knowledge Discovery (1997) 1: 259. doi:10.1023/A:1009748302351

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.

event sequencesfrequent episodessequence analysis
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Copyright information

© Kluwer Academic Publishers 1997