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Efficiently Mining Frequent Trees in a Forest (2002)
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BibTeX
@INPROCEEDINGS{Zaki02efficientlymining,
author = {Mohammed J. Zaki},
title = {Efficiently Mining Frequent Trees in a Forest},
booktitle = {},
year = {2002},
pages = {71--80},
publisher = {ACM press}
}
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Abstract
Mining frequent trees is very useful in domains like bioinformatics, web mining, mining semi-structured data, and so on. We formulate the problem of mining (embedded) subtrees in a forest of rooted, labeled, and ordered trees. We present TreeMiner, a novel algorithm to discover all frequent subtrees in a forest, using a new data structure called scope-list. We contrast TreeMiner with a pattern matching tree mining algorithm (PatternMatcher). We conduct detailed experiments to test the performance and scalability of these methods. We find that TreeMiner outperforms the pattern matching approach by a factor of 4 to 20, and has good scaleup properties. We also present an application of tree mining to analyze real web logs for usage patterns.
