Frequent subgraph mining in outerplanar graphs

Authors:
Tamás Horváth;Jan Ramon;Stefan Wrobel
Affiliations:
Department of Computer Science III, University of Bonn, Bonn, Germany and Fraunhofer Institute IAIS, Schloss Birlinghoven, Sankt Augustin, Germany;Department of Computer Science, Katholieke Universiteit Leuven, Leuven, Belgium;Department of Computer Science III, University of Bonn, Bonn, Germany and Fraunhofer Institute IAIS, Schloss Birlinghoven, Sankt Augustin, Germany
Venue:
Data Mining and Knowledge Discovery
Year:
2010

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Abstract

In recent years there has been an increased interest in frequent pattern discovery in large databases of graph structured objects. While the frequent connected subgraph mining problem for tree datasets can be solved in incremental polynomial time, it becomes intractable for arbitrary graph databases. Existing approaches have therefore resorted to various heuristic strategies and restrictions of the search space, but have not identified a practically relevant tractable graph class beyond trees. In this paper, we consider the class of outerplanar graphs, a strict generalization of trees, develop a frequent subgraph mining algorithm for outerplanar graphs, and show that it works in incremental polynomial time for the practically relevant subclass of well-behaved outerplanar graphs, i.e., which have only polynomially many simple cycles. We evaluate the algorithm empirically on chemo- and bioinformatics applications.