Bipartite Graph Matching for Computing the Edit Distance of Graphs

In the field of structural pattern recognition graphs constitute a very common and powerful way of representing patterns. In contrast to string representations, graphs allow us to describe relational information in the patterns under consideration. One of the main drawbacks of graph representations is that the computation of standard graph similarity measures is exponential in the number of involved nodes. Hence, such computations are feasible for rather small graphs only. One of the most flexible error-tolerant graph similarity measures is based on graph edit distance. In this paper we propose an approach for the efficient compuation of edit distance based on bipartite graph matching by means of Munkres’ algorithm, sometimes referred to as the Hungarian algorithm. Our proposed algorithm runs in polynomial time, but provides only suboptimal edit distance results. The reason for its suboptimality is that implied edge operations are not considered during the process of finding 

• Type: Conference
• Year: 2007
• Where: GBRPR
• Authors: Kaspar Riesen, Michel Neuhaus, Horst Bunke
• Keywords: Edit Distance, GBRPR 2007, Graph Edit Distance, Graph Similarity Measures