A Graduated Assignment Algorithm for Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
A graph distance metric based on the maximal common subgraph
Pattern Recognition Letters
Error Correcting Graph Matching: On the Influence of the Underlying Cost Function
IEEE Transactions on Pattern Analysis and Machine Intelligence
IAM Graph Database Repository for Graph Based Pattern Recognition and Machine Learning
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Approximate graph edit distance computation by means of bipartite graph matching
Image and Vision Computing
Bridging the Gap Between Graph Edit Distance and Kernel Machines
Bridging the Gap Between Graph Edit Distance and Kernel Machines
A survey of graph edit distance
Pattern Analysis & Applications
Multimodal interactive transcription of text images
Pattern Recognition
A comparison of three maximum common subgraph algorithms on a large database of labeled graphs
GbRPR'03 Proceedings of the 4th IAPR international conference on Graph based representations in pattern recognition
Automatic learning of edit costs based on interactive and adaptive graph recognit
GbRPR'11 Proceedings of the 8th international conference on Graph-based representations in pattern recognition
Semantic similarity estimation from multiple ontologies
Applied Intelligence
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Graph Edit Distance is the most widely used measure of similarity between attributed graphs. Given a pair of graphs, it obtains a value of their similarity and also a path that transforms one graph into the other through edit operations. This path can be expressed as a labelling between nodes of both graphs. Important parameters of this measure are the costs of edit operations. In this article, we present new properties of the Graph Edit Distance and we show that its minimization lead to a few different labellings and so, most of the labellings in the labelling space cannot be obtained. Moreover, we present a method that using some of the new properties of the Graph Edit Distance speeds up the computation of all possible labellings.