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.
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Zhou, W., Liu, H., Cheng, H. (2010). Mining Closed Episodes from Event Sequences Efficiently. In: Zaki, M.J., Yu, J.X., Ravindran, B., Pudi, V. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2010. Lecture Notes in Computer Science(), vol 6118. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13657-3_34
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DOI: https://doi.org/10.1007/978-3-642-13657-3_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13656-6
Online ISBN: 978-3-642-13657-3
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