R. Agrawal, T. Imielinski, and A. Swami, Mining association rules between sets of items in large databases, ACM SIGMOD Record, vol.22, issue.2, pp.207-216, 1993.
DOI : 10.1145/170036.170072

R. Agrawal and R. Srikant, Fast algorithms for mining association rules, pp.487-499, 1994.

M. L. Antonie, O. R. Zaiane, and A. Coman, Application of data mining techniques for medical image classification, MDM/KDD, pp.94-101, 2001.

L. Babai and E. M. Luks, Canonical labeling of graphs, Proceedings of the fifteenth annual ACM symposium on Theory of computing , STOC '83, pp.171-183, 1983.
DOI : 10.1145/800061.808746

C. Barat, C. Ducottet, E. Fromont, A. Legrand, and M. Sebban, Weighted Symbols-Based Edit Distance for String-Structured Image Classification, Machine Learning and Knowledge Discovery in Databases, pp.72-86, 2010.
DOI : 10.1007/978-3-642-15880-3_11
URL : https://hal.archives-ouvertes.fr/hal-00499468

C. Borgelt and M. R. Berthold, Mining molecular fragments : Finding relevant substructures of molecules. Data Mining, IEEE International Conference on, p.51, 2002.

S. Brin, R. Motwani, J. D. Ullman, and S. Tsur, Dynamic itemset counting and implication rules for market basket data, Proceedings of the 1997 ACM SIGMOD international conference on Management of data -SIGMOD '97, pp.255-264, 1997.

E. Brisson, Representing geometric structures in d dimensions : topology and order, SCG, pp.218-227, 1989.

H. Cheng, X. Yan, J. Han, and C. W. Hsu, Discriminative Frequent Pattern Analysis for Effective Classification, 2007 IEEE 23rd International Conference on Data Engineering, pp.716-725, 2007.
DOI : 10.1109/ICDE.2007.367917

R. Cori, Un code pour les graphes planaires et ses applications, Astérisque, 1975.

G. Damiand, Y. Bertrand, and C. Fiorio, Topological model for twodimensional image representation : definition and optimal extraction algorithm, CVIU, vol.93, issue.2, pp.111-154, 2004.
URL : https://hal.archives-ouvertes.fr/lirmm-00137917

G. Damiand, C. De-la-higuera, J. Janodet, E. Samuel, and C. Solnon, A Polynomial Algorithm for Submap Isomorphism, GbR), pp.102-112, 2009.
DOI : 10.1007/978-3-540-74970-7_51

G. Damiand, Contributions aux Cartes Combinatoires et Cartes Généralisées : Simplification, Modèles, Invariants Topologiques et Applications . Habilitation à diriger des recherches, 2010.

G. Damiand, C. Solnon, C. De-la-higuera, J. C. Janodet, and É. Samuel, Polynomial algorithms for subisomorphism of nD open combinatorial maps, Computer Vision and Image Understanding, vol.115, issue.7, pp.1374-1383, 2011.
DOI : 10.1016/j.cviu.2010.12.013
URL : https://hal.archives-ouvertes.fr/hal-00597483

M. Deshp, M. Kuramochi, and G. Karypis, Frequent substructure-based approaches for classifying chemical compounds, Computing, pp.1-15, 2003.

J. Edmonds, A combinatorial representation for polyhedral surfaces. Notices of the, 1960.

E. Escovar and M. Biajiz, SSDM : A Semantically Similar Data Mining Algorithm, 20th Brazilian Symposium of, 2005.

M. Everingham, L. Van-gool, C. K. Williams, J. Winn, and A. Zisserman, The Pascal Visual Object Classes (VOC) Challenge, International Journal of Computer Vision, vol.73, issue.2, pp.303-338, 2010.
DOI : 10.1007/s11263-009-0275-4

U. Fayyad, G. P. Shapiro, and P. Smyth, From data mining to knowledge discovery : an overview. AI Magazine, pp.37-54, 1996.

D. Gay, Calcul de motifs sous contraintes pour la classification supervisée, Thèse de doctorat en informatique, 2009.

S. Gosselin, G. Damiand, and C. Solnon, Signatures of Combinatorial Maps, 13th International Workshop on Combinatorial Image Analysis (IWCIA), pp.370-382, 2009.
DOI : 10.1007/978-3-642-10210-3_29
URL : https://hal.archives-ouvertes.fr/hal-00457234

S. Gosselin, G. Damiand, and C. Solnon, Recherche efficace dans une base de cartes combinatoires, RFIA, 2010.
URL : https://hal.archives-ouvertes.fr/hal-01381448

S. Gosselin, G. Damiand, and C. Solnon, Efficient search of combinatorial maps using signatures, Theoretical Computer Science, vol.412, issue.15, pp.1392-1405, 2011.
DOI : 10.1016/j.tcs.2010.10.029
URL : https://hal.archives-ouvertes.fr/hal-00567332

S. Gosselin, G. Damiand, and C. Solnon, Frequent Submap Discovery, 22nd Annual Symposium on Combinatorial Pattern Matching (CPM2011), 2011.
DOI : 10.4153/CJM-1963-029-x
URL : https://hal.archives-ouvertes.fr/hal-00636373

]. J. Han, J. Pei, and Y. Yin, Mining frequent patterns without candidate generation, ACM SIGMOD Record, vol.29, issue.2, pp.1-12, 2000.
DOI : 10.1145/335191.335372
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.35.2678

M. Houtsma, Set-oriented mining for association rules in relational databases, Proceedings of the Eleventh International Conference on Data Engineering, pp.25-33, 1995.
DOI : 10.1109/ICDE.1995.380413

J. Huan, W. Wang, and J. Prins, Efficient mining of frequent subgraphs in the presence of isomorphism, Third IEEE International Conference on Data Mining, pp.549-552, 2003.
DOI : 10.1109/ICDM.2003.1250974

A. Inokuchi, T. Washio, and H. Motoda, An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data, pp.13-23, 2000.
DOI : 10.1007/3-540-45372-5_2

A. Jacques, Constellations et graphes topologiques, Combinatorial Theory and Applications, pp.657-673, 1970.

M. Kuramochi and G. Karypis, Frequent subgraph discovery. Data Mining, p.313, 2001.
DOI : 10.1109/icdm.2001.989534
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.20.7488

W. Li, J. Han, and J. Pei, CMAR : Accurate and efficient classification based on multiple class-association rules, icdm, p.369, 2001.

P. Lienhardt, -dimensional generalized maps, Proceedings of the fifth annual symposium on Computational geometry , SCG '89, pp.228-236, 1989.
DOI : 10.1145/73833.73859
URL : https://hal.archives-ouvertes.fr/hal-00909382

P. Lienhardt, Topological models for boundary representation: a comparison with n-dimensional generalized maps, Computer-Aided Design, vol.23, issue.11, pp.59-82, 1991.
DOI : 10.1016/0010-4485(91)90100-B

P. Lienhardt, N-DIMENSIONAL GENERALIZED COMBINATORIAL MAPS AND CELLULAR QUASI-MANIFOLDS, International Journal of Computational Geometry & Applications, vol.04, issue.03, pp.275-324, 1994.
DOI : 10.1142/S0218195994000173

. Dao-i-lin, Pincer-Search : A New Algorithm for Discovering the Maximum Frequent Set 2 Association Rule Mining, pp.1-17, 1997.

J. Lin, Mining association rules : Anti-skew algorithms. Data Engineering, Proceedings, pp.486-493, 1998.

B. Liu, W. Hsu, and Y. Ma, Integrating classification and association rule mining. Knowledge discovery and data mining, pp.80-86, 1998.

C. Lucchese, S. Orlando, P. Palmerini, and R. Perego, kDCI : A multi-strategy algorithm for mining frequent sets, Proc. of ICDM Conf, 2003.

J. Macqueen and O. , Some methods for classification and analysis of multivariate observations, Proceedings of the fifth Berkeley symposium on mathematical statistics and probability, p.14, 1967.

V. Malleron and V. Eglin, A Mixed Approach for Handwritten Documents Structural Analysis, 2011 International Conference on Document Analysis and Recognition, 2011.
DOI : 10.1109/ICDAR.2011.62
URL : https://hal.archives-ouvertes.fr/hal-01354452

C. Moulin, C. Barat, and C. Ducottet, Fusion of tf. idf weighted bag of visual features for image classification, Content-Based Multimedia Indexing (CBMI), 2010 International Workshop on, pp.1-6, 2010.
URL : https://hal.archives-ouvertes.fr/ujm-00501523

A. Mueller, Fast Sequential and Parallel Algorithms for Association Rule Mining : Table of Contents. Knowledge Creation Diffusion Utilization, pp.571-76, 1995.

S. Nijssen and J. Kok, The Gaston Tool for Frequent Subgraph Mining, Electronic Notes in Theoretical Computer Science, vol.127, issue.1, pp.77-87, 2005.
DOI : 10.1016/j.entcs.2004.12.039

E. Omiecinski, An Efficient Algorithm for Mining Databases Association Rules in Large, Technology, pp.432-444

J. Soo-park, M. Chen, and P. S. Yu, An effective hash-based algorithm for mining association rules, ACM SIGMOD Record, vol.24, issue.2, pp.175-186, 1995.
DOI : 10.1145/568271.223813

A. Prado, B. Jeudy, E. Fromont, and F. Diot, PLAGRAM : un algorithme de fouille de graphes plans efficace, CAp, pp.343-359, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00618764

A. Rosenfeld, Adjacency in digital pictures, Information and Control, vol.26, issue.1, pp.24-33, 1974.
DOI : 10.1016/S0019-9958(74)90696-2

L. Steven and . Salzberg, C4.5 : Programs for machine learning by j. ross quinlan, Machine Learning, pp.235-240, 1993.

É. Samuel, C. De-la-higuera, and J. Janodet, Extracting Plane Graphs from Images, Structural, Syntactic , and Statistical Pattern Recognition, pp.233-243, 2010.
DOI : 10.1007/978-3-642-14980-1_22
URL : https://hal.archives-ouvertes.fr/ujm-00531224

A. Ta, C. Wolf, G. Lavoue, and A. Baskurt, Recognizing and localizing individual activities through graph matching. Advanced Video and Signal Based Surveillance, IEEE Conference on, vol.0, pp.196-203, 2010.
DOI : 10.1109/avss.2010.81
URL : https://hal.archives-ouvertes.fr/hal-01381516

H. Toivonen, Sampling large databases for association rules, of the International Conference on Very Large Data, pp.134-145, 1996.

W. T. Tutte, A census of planar maps. Canad, J. Math, vol.15, pp.249-271, 1963.

M. Wörlein, T. Meinl, I. Fischer, M. Philippsen, F. et al., A quantitative comparison of the subgraph miners MoFa, gSpan, Knowledge Discovery in Databases : PKDD 2005, pp.392-403, 2005.

X. Yan and J. Han, gspan : Graph-based substructure pattern mining, Proceedings of the 2002 IEEE International Conference on Data Mining, ICDM '02, p.721, 2002.

X. Yan, P. S. Yu, and J. Han, Graph indexing : A frequent structurebased approach Graph indexing based on discriminative frequent structure analysis, Proceedings of the 2004 ACM SIGMOD international conference on Management of data, pp.346960-993, 2004.

X. Yan, P. S. Yu, and J. Han, Substructure similarity search in graph databases, Proceedings of the 2005 ACM SIGMOD international conference on Management of data , SIGMOD '05, pp.766-777, 2005.
DOI : 10.1145/1066157.1066244

M. J. Zaki, Scalable algorithms for association mining. Knowledge and Data Engineering, IEEE Transactions on, vol.12, issue.3, pp.372-390, 2000.

M. J. Zaki, . Parthasarathy, . Ogihara, and O. Li, New algorithms for fast discovery of association rules, 3rd Intl. Conf. on Knowledge Discovery and Data Mining, pp.283-286, 1997.