SIMILARITY MEASURES FOR HIERARCHICAL REPRESENTATIONS OF GRAPHS WITH UNIQUE NODE LABELS
Peter J. C. Dickinson, M. Kraetzl, Horst Bunke, Michel Neuhaus, Arek Dadej · International Journal of Pattern Recognition and Artificial Intelligence · 2004
A hierarchical abstraction scheme based on node contraction and two related similarity measures for graphs with unique node labels are proposed in this paper. The contraction scheme reduces the number of nodes in a graph and leads to a speed-up in the computation of graph similarity. Theoretical properties of the new graph similarity measures are derived and experimentally verified. A potential application of the proposed graph abstraction scheme in the domain of computer network monitoring is discussed.