DryadeParent, An Efficient and Robust Closed Attribute Tree Mining Algorithm

Authors:
Alexandre Termier;Marie-Christine Rousset;Michele Sebag;Kouzou Ohara;Takashi Washio;Hiroshi Motoda
Affiliations:
-;-;-;-;-;-
Venue:
IEEE Transactions on Knowledge and Data Engineering
Year:
2008

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Abstract

In this paper, we present a new tree mining algorithm, DryadeParent, based on the hooking principle first introduced in Dryade. In the experiments, we demonstrate that the branching factor and depth of the frequent patterns to find are key factors of complexity for tree mining algorithms, even if often overlooked in previous work. We show that DryadeParent outperforms the current fastest algorithm, CMTreeMiner, by orders of magnitude on datasets where the frequent patterns have a high branching factor.