A survey of graph edit distance

@article{Gao2008ASO,
  title={A survey of graph edit distance},
  author={Xinbo Gao and Bing Xiao and Dacheng Tao and Xuelong Li},
  journal={Pattern Analysis and Applications},
  year={2008},
  volume={13},
  pages={113-129}
}
Inexact graph matching has been one of the significant research foci in the area of pattern analysis. As an important way to measure the similarity between pairwise graphs error-tolerantly, graph edit distance (GED) is the base of inexact graph matching. The research advance of GED is surveyed in order to provide a review of the existing literatures and offer some insights into the studies of GED. Since graphs may be attributed or non-attributed and the definition of costs for edit operations… 
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TLDR
A generalized version of the existing approximation framework using an iterative bipartite procedure is introduced and it is shown that the extension substantially improves the accuracy of the approximations while the run time is increased only linearly with the number of additional iterations.
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TLDR
This paper proposes a novel convolution graph kernel, which differs from other graph kernels mainly in that it is closely related to error-tolerant graph edit distance and can therefore be applied to attributed graphs of various kinds.
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TLDR
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TLDR
This work proposes a cost inference method that is based on a distribution estimation of edit operations that employs an expectation maximization algorithm to learn mixture densities from a labeled sample of graphs and derive edit costs that are subsequently applied in the context of a graph edit distance computation framework.
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TLDR
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TLDR
A binary linear programming formulation of the graph edit distance for unweighted, undirected graphs with vertex attributes is derived and applied to a graph recognition problem, and the new metric is shown to perform quite well in comparison to existing metrics when applications to a database of chemical graphs.
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TLDR
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