Fast Suboptimal Algorithms for the Computation of Graph Edit Distance
Graph edit distance is one of the most flexible mechanisms for error-tolerant graph matching. Its key advantage is that edit distance is applicable to unconstrained attributed graphs and can be tailored to a wide variety of applications by means of specific edit cost functions. Its computational complexity, however, is exponential in the number of vertices, which means that edit distance is feasible for small graphs only. In this paper, we propose two simple, but effective modifications of a standard edit distance algorithm that allow us to suboptimally compute edit distance in a faster way. In experiments on real data, we demonstrate the resulting speedup and show that classification accuracy is mostly not affected. The suboptimality of our methods mainly results in larger inter-class distances, while intra-class distances remain low, which makes the proposed methods very well applicable to distance-based graph classification.
- 2.Hopcroft, J., Wong, J.: Linear time algorithm for isomorphism of planar graphs. In: Proc. 6th Annual ACM Symposium on Theory of Computing, pp. 172–184 (1974)Google Scholar
- 8.Neuhaus, M., Bunke, H.: An error-tolerant approximate matching algorithm for attributed planar graphs and its application to fingerprint classification. In: Fred, A., Caelli, T.M., Duin, R.P.W., Campilho, A.C., de Ridder, D. (eds.) SSPR&SPR 2004. LNCS, vol. 3138, pp. 180–189. Springer, Heidelberg (2004)CrossRefGoogle Scholar
- 9.Hlaoui, A., Wang, S.: A node-mapping-based algorithm for graph matching (to appear, 2006)Google Scholar