DocumentCode :
2866466
Title :
Efficient mining of high branching factor attribute trees
Author :
Termier, Alexandre ; Rousset, Marie-Christine ; Sebag, Michèle ; Ohara, Kouzou ; Washio, Takashi ; Motoda, Hiroshi
Author_Institution :
I.S.I.R., Osaka Univ., Japan
fYear :
2005
fDate :
27-30 Nov. 2005
Abstract :
In this paper, we present a new tree mining algorithm, DryadeParent, based on the hooking principle first introduced in Dryade (Termier et al, 2004). In the experiments, we demonstrate that the branching factor and depth of the frequent patterns to find are key factor of complexity for tree mining algorithms. 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.
Keywords :
computational complexity; data mining; trees (mathematics); CMTreeMiner; DryadeParent; algorithm complexity; efficient tree mining; frequent pattern depth; high branching factor attribute trees; hooking principle; Data mining; Itemsets; Labeling; Tree graphs;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Mining, Fifth IEEE International Conference on
ISSN :
1550-4786
Print_ISBN :
0-7695-2278-5
Type :
conf
DOI :
10.1109/ICDM.2005.55
Filename :
1565782
Link To Document :
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