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Mining Interpretable Subgraphs

ECML/PKDD Workshop on Mining and Learning with Graphs, 2006.
Authors: Siegfried Nijssen
URL: http://www.inf.uni-konstanz.de/mlg2006/07.pdf
Tags: 2006 graphs workshop
Abstract: We present a measure that estimates the interpretability of a frequent subgraph. We show that a feature selection algorithm that uses this measure creates a set of features that is smaller and equally predictive as features obtained in earlier studies. A significant number of the selected features turn out to be trees or cyclic graphs, leading us to the conclusion that such features are not as useless as suggested in some earlier studies. Finally, we show that a constraint on this measure can be pushed in the mining process, thus leading to faster discovery of interesting subgraphs.
| URL | BibTeX  
@inproceedings{Nijssen:06,
title = {Mining Interpretable Subgraphs},
author = {Siegfried Nijssen},
booktitle = {ECML/PKDD Workshop on Mining and Learning with Graphs},
url = {http://www.inf.uni-konstanz.de/mlg2006/07.pdf},
year = {2006},
abstract = {We present a measure that estimates the interpretability of a frequent subgraph. We show that a feature selection algorithm that uses this measure creates a set of features that is smaller and equally predictive as features obtained in earlier studies. A significant number of the selected features turn out to be trees or cyclic graphs, leading us to the conclusion that such features are not as useless as suggested in some earlier studies. Finally, we show that a constraint on this measure can be pushed in the mining process, thus leading to faster discovery of interesting subgraphs.},
keywords = {2006 graphs workshop }
}