Mining closed episodes from event sequences efficiently

Authors:
Wenzhi Zhou;Hongyan Liu;Hong Cheng
Affiliations:
Department of Management Science and Engineering, Tsinghua University, Beijing, China;Department of Management Science and Engineering, Tsinghua University, Beijing, China;Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Hong Kong
Venue:
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
Year:
2010

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Abstract

Recent studies have proposed different methods for mining frequent episodes. In this work, we study the problem of mining closed episodes based on minimal occurrences. We study the properties of minimal occurrences and design effective pruning techniques to prune non-closed episodes. An efficient mining algorithm Clo_episode is proposed to mine all closed episodes following a breadth-first search order and integrating the pruning techniques. Experimental results demonstrate the efficiency of our mining algorithm and the compactness of the mining result set.