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Fast algorithms for frequent episode discovery in event sequences

Laxman, Srivatsan and Sastry, PS and Unnikrishnan, KP (2004) Fast algorithms for frequent episode discovery in event sequences. In: Proc. Third Int. Workshop on Mining Temporal and Sequential Data, August 2004, Sigkdd, Seattle, WA.

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In this paper we consider the process of discovering frequent episodes in event sequences. The most computationally intensive part of this process is that of counting the frequencies of a set of candidate episodes. We present two new frequency counting algorithms for speeding up this part. These, referred to as non-overlapping and non-inteleaved frequency counts, are based on directly counting suitable subsets of the occurrences of an episode. Hence they are different from the frequency counts of Mannila et al [1], where they count the number of windows in which the episode occurs. Our new frequency counts offer a speed-up factor of 7 or more on real and synthetic datasets. We also show how the new frequency counts can be used when the events in episodes have time-durations as well.

Item Type: Conference Paper
Publisher: ACM Press
Additional Information: Copyright of this article belongs to ACM Press.
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 22 Mar 2012 08:22
Last Modified: 22 Mar 2012 08:22
URI: http://eprints.iisc.ac.in/id/eprint/44043

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