L. Brun, B. Gaüzère, and S. Fourey, Relationships between Graph Edit Distance and Maximal Common Unlabeled Subgraph, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00714879

. Werneck, Learning Cost Functions for Graph Matching
URL : https://hal.archives-ouvertes.fr/hal-01889964

H. Bunke, On a relation between graph edit distance and maximum common subgraph, Pattern Recognition Letters, vol.18, issue.8, pp.689-694, 1997.

H. Bunke and G. Allermann, Inexact graph matching for structural pattern recognition, Pattern Recognition Letters, vol.1, issue.4, pp.245-253, 1983.

H. Bunke, S. Günter, and X. Jiang, Towards bridging the gap between statistical and structural pattern recognition: Two new concepts in graph matching, Proceedings of the Second International Conference on Advances in Pattern Recognition, pp.1-11, 2001.

H. Bunke and K. Riesen, Recent advances in graph-based pattern recognition with applications in document analysis, Pattern Recognition, vol.44, issue.5, pp.1057-1067, 2011.

T. S. Caetano, J. J. Mcauley, L. Cheng, Q. V. Le, and A. J. Smola, Learning graph matching, IEEE Trans. Pattern Anal. Mach. Intell, vol.31, issue.6, pp.1048-1058, 2009.

M. Cho, K. Alahari, and J. Ponce, Learning graphs to match, IEEE International Conference on Computer Vision, ICCV 2013, pp.25-32, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00875105

X. Cortés and F. Serratosa, Learning graph-matching edit-costs based on the optimality of the oracle's node correspondences, Pattern Recognition Letters, vol.56, pp.22-29, 2015.

X. Cortés and F. Serratosa, Learning graph matching substitution weights based on the ground truth node correspondence, IJPRAI, vol.30, issue.2, 2016.

H. W. Kuhn and B. Yaw, The hungarian method for the assignment problem, Naval Res. Logist. Quart, pp.83-97, 1955.

M. Leordeanu, R. Sukthankar, and M. Hebert, Unsupervised learning for graph matching, International Journal of Computer Vision, vol.96, issue.1, pp.28-45, 2012.

M. Neuhaus and H. Bunke, Self-organizing maps for learning the edit costs in graph matching, IEEE Trans. Systems, Man, and Cybernetics, vol.35, issue.3, pp.503-514, 2005.

M. Neuhaus and H. Bunke, Automatic learning of cost functions for graph edit distance, Information Sciences, vol.177, issue.1, pp.239-247, 2007.

M. Neuhaus and H. Bunke, Bridging the Gap Between Graph Edit Distance and Kernel Machines, 2007.

K. Riesen, H. Bunke, N. Da-vitoria-lobo, T. Kasparis, F. Roli et al., Iam graph database repository for graph based pattern recognition and machine learning, Structural, Syntactic, and Statistical Pattern Recognition, pp.287-297, 2008.

K. Riesen and M. Ferrer, Predicting the correctness of node assignments in bipartite graph matching, Pattern Recognition Letters, vol.69, pp.8-14, 2016.

J. M. De-sa, Pattern Recognition: Concepts, Methods, and Applications, 2001.

F. B. Silva, O. De, R. Werneck, S. Goldenstein, S. Tabbone et al., Graph-based bag-of-words for classification, Pattern Recognition, vol.74, pp.266-285, 2018.
URL : https://hal.archives-ouvertes.fr/hal-02073440

D. R. Wilson and T. R. Martinez, Improved heterogeneous distance functions, J. Artif. Int. Res, vol.6, issue.1, pp.1-34, 1997.