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