Title :
DryadeParent, An Efficient and Robust Closed Attribute Tree Mining Algorithm
Author :
Termier, Alexandre ; Rousset, Marie-Christine ; Sebag, Michéle ; Ohara, Kouzou ; Washio, Takashi ; Motoda, Hiroshi
Author_Institution :
Univ. of Grenoble, St. Martin d´´Heres
fDate :
3/1/2008 12:00:00 AM
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 data sets where the frequent tree patterns have a high branching factor.
Keywords :
data mining; tree data structures; CMTreeMiner; DRYADEPARENT; branching factor; hooking principle; robust closed attribute tree mining algorithm; Data mining; Mining methods and algorithms; Mining tree structured data;
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
DOI :
10.1109/TKDE.2007.190695