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Fourth IEEE International Conference on Data Mining (ICDM'04)
Matching in Frequent Tree Discovery
Brighton, United Kingdom
November 01-November 04
ISBN: 0-7695-2142-8
ASCII Text
x 
 
Bj? Bringmann, "Matching in Frequent Tree Discovery," Data Mining, IEEE International Conference on, pp. 335-338, Fourth IEEE International Conference on Data Mining (ICDM'04), 2004.
 
 
BibTex
x
 
@article{ 10.1109/ICDM.2004.10064,
author = {Bj? Bringmann},
title = {Matching in Frequent Tree Discovery},
journal ={Data Mining, IEEE International Conference on},
volume = {0},
year = {2004},
isbn = {0-7695-2142-8},
pages = {335-338},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICDM.2004.10064},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Data Mining, IEEE International Conference on
TI - Matching in Frequent Tree Discovery
SN - 0-7695-2142-8
SP335
EP338
A1 - Bj? Bringmann,
PY - 2004
KW - null
VL - 0
JA - Data Mining, IEEE International Conference on
ER -
 
Bj? Bringmann, University of Freiburg, Germany
Various definitions and frameworks for discovering frequent trees in forests have been developed recently. 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 novel 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.
Citation:
Bj? Bringmann, "Matching in Frequent Tree Discovery," icdm, pp.335-338, Fourth IEEE International Conference on Data Mining (ICDM'04), 2004
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