Discovery of Frequent Episodes in Event Sequences

  • Authors:
  • Heikki Mannila;Hannu Toivonen;A. Inkeri Verkamo

  • Affiliations:
  • Department of Computer Science, P.O. Box 26, FIN-00014 University of Helsinki, Finland. E-mail: heikki.mannila@cs.helsinki.fi, hannu.toivonen@cs.helsinki.fi, inkeri.verkamo@cs.helsinki.fi;Department of Computer Science, P.O. Box 26, FIN-00014 University of Helsinki, Finland. E-mail: heikki.mannila@cs.helsinki.fi, hannu.toivonen@cs.helsinki.fi, inkeri.verkamo@cs.helsinki.fi;Department of Computer Science, P.O. Box 26, FIN-00014 University of Helsinki, Finland. E-mail: heikki.mannila@cs.helsinki.fi, hannu.toivonen@cs.helsinki.fi, inkeri.verkamo@cs.helsinki.fi

  • Venue:
  • Data Mining and Knowledge Discovery
  • Year:
  • 1997

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Abstract

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