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2004
ACM

Frequent free tree discovery in graph data

10 years 4 months ago
Frequent free tree discovery in graph data
In recent years, researchers in graph mining have been exploring linear paths as well as subgraphs as pattern languages. In this paper, we are investigating the middle ground between these two extremes: mining free (that is, unrooted) trees in graph data. The motivation for this is the need to upgrade linear path patterns, while avoiding complexity issues with subgraph patterns. Starting from such complexity considerations, we are defining free trees and their canonical form, before we present FreeTreeMiner, an algorithm making efficient use of this canonical form during search. Experiments with two datasets from the National Cancer Institute’s Developmental Therapeutics Program (DTP), anti-HIV and anti-cancer screening data, are reported.
Ulrich Rückert, Stefan Kramer
Added 30 Jun 2010
Updated 30 Jun 2010
Type Conference
Year 2004
Where SAC
Authors Ulrich Rückert, Stefan Kramer
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