Matching in Frequent Tree Discovery

Authors:
Bjorn Bringmann
Affiliations:
University of Freiburg, Germany
Venue:
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Year:
2004

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Abstract

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.