DocumentCode :
2850637
Title :
Matching in frequent tree discovery
Author :
Bringmann, Björn
Author_Institution :
Lab. of Machine Learning, Freiburg Univ., Germany
fYear :
2004
fDate :
1-4 Nov. 2004
Firstpage :
335
Lastpage :
338
Abstract :
Various definitions and frameworks for discovering frequent trees in forests have been developed. At the heart of these frameworks lies the notion of matching, which determines when a pattern tree matches a tree in a data set. We introduce a notion of tree matching for use in frequent tree mining and we show that it generalizes the framework of Zaki while still being more specific than that of Termier et al. Furthermore, we show how Zaki´s TreeMinerV algorithm can be adapted towards our notion of tree matching. Experiments show the promise of the approach.
Keywords :
data mining; pattern matching; trees (mathematics); TreeMinerV algorithm; frequent tree discovery; tree matching; tree mining; Databases; Formal languages; Frequency; Heart; Machine learning; Pattern matching; Tree graphs; Web mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Mining, 2004. ICDM '04. Fourth IEEE International Conference on
Print_ISBN :
0-7695-2142-8
Type :
conf
DOI :
10.1109/ICDM.2004.10064
Filename :
1410304
Link To Document :
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