R. 1. Bilenko, M. Basu, S. Mooney, and R. J. , Integrating constraints and metric learning in semi-supervised clustering, Twenty-first international conference on Machine learning , ICML '04, 2004.
DOI : 10.1145/1015330.1015360
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.5745

M. Schultz and T. Joachims, Learning a distance metric from relative comparisons, Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, NIPS 2003, 2003.

K. Kummamuru, R. Krishnapuram, and R. Agrawal, On Learning Asymmetric Dissimilarity Measures, Fifth IEEE International Conference on Data Mining (ICDM'05), pp.697-700, 2005.
DOI : 10.1109/ICDM.2005.107

S. Bayoudh, L. Miclet, and A. Delhay, Learning by analogy: A classification rule for binary and nominal data, In: IJCAI, pp.678-683, 2007.

R. Wagner and M. Fisher, The String-to-String Correction Problem, Journal of the ACM, vol.21, issue.1, 1974.
DOI : 10.1145/321796.321811

J. Oncina and M. Sebban, Learning stochastic edit distance: Application in handwritten character recognition, Pattern Recognition, vol.39, issue.9, 2006.
DOI : 10.1016/j.patcog.2006.03.011
URL : https://hal.archives-ouvertes.fr/hal-00114106

S. Ristad and P. Yianilos, Learning string-edit distance, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.20, issue.5, pp.522-532, 1998.
DOI : 10.1109/34.682181
URL : http://arxiv.org/abs/cmp-lg/9610005

M. Bernard, A. Habrard, and M. Sebban, Learning Stochastic Tree Edit Distance, Proc. of ECML'06, pp.4212-4254, 2006.
DOI : 10.1007/11871842_9
URL : https://hal.archives-ouvertes.fr/ujm-00109696

S. Selkow, The tree-to-tree editing problem, Information Processing Letters, vol.6, issue.6, pp.184-186, 1977.
DOI : 10.1016/0020-0190(77)90064-3

K. Zhang and D. Shasha, Simple Fast Algorithms for the Editing Distance between Trees and Related Problems, SIAM Journal on Computing, vol.18, issue.6, pp.1245-1262, 1989.
DOI : 10.1137/0218082

J. Jolion, Some Experiments on Clustering a Set of Strings, 4th IAPR International Workshop on Graph based Representations, pp.214-224, 2003.
DOI : 10.1007/3-540-45028-9_19

P. Klein, Computing the Edit-Distance Between Unrooted Ordered Trees, Proc. of the 6th European Symposium on Algorithms (ESA), pp.91-102, 1998.
DOI : 10.1007/3-540-68530-8_8

P. Bille, A survey on tree edit distance and related problems, Theoretical Computer Science, vol.337, issue.1-3, pp.217-239, 2005.
DOI : 10.1016/j.tcs.2004.12.030
URL : http://doi.org/10.1016/j.tcs.2004.12.030

A. Dempster, M. Laird, and D. Rubin, Maximum likelihood from incomplete data via the EM algorithm, J. R. Stat. Soc B, issue.39, pp.1-38, 1977.

A. Pentland, R. Picard, and S. Sclaroff, Photobook: Tools for content-based manipulation of image databases In: SPIE Storage and Retrieval of Image and Video Databases, pp.18-32, 1995.

J. Wang, J. Li, and G. Wiederhold, SIMPLIcity: semantics-sensitive integrated matching for picture libraries, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.23, issue.9, pp.947-963, 2001.
DOI : 10.1109/34.955109
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.29.3735

C. Carson, S. Belongie, H. Greenspan, and J. Malik, Blobworld: image segmentation using expectation-maximization and its application to image querying, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.24, issue.8, pp.1026-1038, 2002.
DOI : 10.1109/TPAMI.2002.1023800

E. Gómez, L. Micó, and J. Oncina, Testing the linear approximating eliminating search algorithm in handwritten character recognition tasks, VI Symposium Nacional de reconocimiento de Formas y Análisis de Imágenes, pp.212-217, 1995.