Statistical significance of episodes with general partial orders

Achar, Avinash and Sastry, PS (2015) Statistical significance of episodes with general partial orders. In: INFORMATION SCIENCES, 296 . pp. 175-200.

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Abstract

Frequent episode discovery is one of the methods used for temporal pattern discovery in sequential data. An episode is a partially ordered set of nodes with each node associated with an event type. For more than a decade, algorithms existed for episode discovery only when the associated partial order is total (serial episode) or trivial (parallel episode). Recently, the literature has seen algorithms for discovering episodes with general partial orders. In frequent pattern mining, the threshold beyond which a pattern is inferred to be interesting is typically user-defined and arbitrary. One way of addressing this issue in the pattern mining literature has been based on the framework of statistical hypothesis testing. This paper presents a method of assessing statistical significance of episode patterns with general partial orders. A method is proposed to calculate thresholds, on the non-overlapped frequency, beyond which an episode pattern would be inferred to be statistically significant. The method is first explained for the case of injective episodes with general partial orders. An injective episode is one where event-types are not allowed to repeat. Later it is pointed out how the method can be extended to the class of all episodes. The significance threshold calculations for general partial order episodes proposed here also generalize the existing significance results for serial episodes. Through simulations studies, the usefulness of these statistical thresholds in pruning uninteresting patterns is illustrated. (C) 2014 Elsevier Inc. All rights reserved.

Item Type:	Journal Article
Publication:	INFORMATION SCIENCES
Publisher:	ELSEVIER SCIENCE INC
Additional Information:	Copyright for this article belongs to the ELSEVIER SCIENCE INC, 360 PARK AVE SOUTH, NEW YORK, NY 10010-1710 USA
Keywords:	Episode discovery; Partial order episodes; Non-overlapped frequency; Statistical significance
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	14 Feb 2015 13:32
Last Modified:	14 Feb 2015 13:32
URI:	http://eprints.iisc.ac.in/id/eprint/50802

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