2002 EfficientlyMiningFrequentTreesi

• (Zaki, 2002) ⇒ Mohammed J. Zaki. (2002). “Efficiently Mining Frequent Trees in a Forest.” In: Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2002). doi:10.1145/775047.775058

Subject Headings: Frequent Tree Mining.

Cited By

• http://scholar.google.com/scholar?q=%22Efficiently+mining+frequent+trees+in+a+forest%22+2002
• http://dl.acm.org/citation.cfm?id=775047.775058&preflayout=flat#citedby

Quotes

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.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2002 EfficientlyMiningFrequentTreesi	Mohammed J. Zaki			Efficiently Mining Frequent Trees in a Forest				10.1145/775047.775058