D. Auber, Y. Chiricota, F. Jourdan, and G. Melancon, Multiscale visualization of small world networks, IEEE Symposium on Information Visualization 2003 (IEEE Cat. No.03TH8714), pp.75-81, 2003.
DOI : 10.1109/INFVIS.2003.1249011
URL : https://hal.archives-ouvertes.fr/lirmm-00269770

U. Brandes, M. Gaertler, and D. Wagner, Engineering graph clustering: Models and experimental evaluation, ACM Journal of Experimental Algorithmics, vol.12, 2007.

D. G. Corneil and C. C. Gotlieb, An Efficient Algorithm for Graph Isomorphism, Journal of the ACM, vol.17, issue.1, pp.51-64, 1970.
DOI : 10.1145/321556.321562

A. Gavin, M. Bosche, R. Krause, P. Grandi, M. Marzioch et al., Superti-Furga. Functional organization of the yeast proteome by systematic analysis of protein complexes, Nature, issue.6868, pp.415141-147, 2002.

M. Girvan and M. E. Newman, Community structure in social and biological networks, Proc. Natl. Acad. Sci. USA, pp.8271-8276, 2002.
DOI : 10.1073/pnas.122653799

M. Halkidi, Y. Batistakis, and M. Vazirgiannis, Cluster validity methods, ACM SIGMOD Record, vol.31, issue.2, 2002.
DOI : 10.1145/565117.565124

M. Halkidi and M. Vazirgiannis, Clustering validity assessment: finding the optimal partitioning of a data set, Proceedings 2001 IEEE International Conference on Data Mining, 2001.
DOI : 10.1109/ICDM.2001.989517

A. K. Jain, M. N. Murty, and P. J. Flynn, Data clustering: a review, ACM Computing Surveys, vol.31, issue.3, pp.264-323, 1999.
DOI : 10.1145/331499.331504

R. Kannan, S. Vempala, and A. Vetta, On clusterings-good, bad and spectral, Proceedings 41st Annual Symposium on Foundations of Computer Science, pp.497-515, 2004.
DOI : 10.1109/SFCS.2000.892125

V. Lacroix, C. Fernandes, and M. Sagot, Motif Search in Graphs: Application to Metabolic Networks, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.3, issue.4, pp.360-368, 2006.
DOI : 10.1109/TCBB.2006.55
URL : https://hal.archives-ouvertes.fr/hal-00427984

O. Maimon and L. Rokach, Data Mining and Knowledge Discovery Handbook, 2005.

M. Mihail, C. Gkantsidis, A. Saberi, and E. Zegura, On the semantics of internet topologies, tech. rep. gitcc0207, 2002.

G. W. Milligan, A monte-carlo study of 30 internal criterion measures for clusteranalysis . Psychometrica, pp.187-195, 1981.

B. Mitchell, M. S. , Y. C. , and G. E. Bunch, A clustering tool for the recovery and maintenance of software system structures, International Conference on Software Maintenance, ICSM, 1999.

M. E. Newman and M. Girvan, Finding and evaluating community structure in networks, Physical Review E, vol.69, issue.2, 2004.
DOI : 10.1103/PhysRevE.69.026113

M. E. Newman, Fast algorithm for detecting community structure in networks, Physical Review E, vol.69, issue.6, p.66133, 2004.
DOI : 10.1103/PhysRevE.69.066133

M. E. Newman, Finding community structure in networks using the eigenvectors of matrices, Physical Review E, vol.74, issue.3, 2006.
DOI : 10.1103/PhysRevE.74.036104

Q. H. Nguyen, V. J. Rayward, and . Smith, Internal quality measures for clustering in metric spaces, International Journal of Business Intelligence and Data Mining, vol.3, issue.1, pp.4-29, 2008.
DOI : 10.1504/IJBIDM.2008.017973

W. M. Rand, Objective Criteria for the Evaluation of Clustering Methods, Journal of the American Statistical Association, vol.15, issue.336, pp.846-850, 1971.
DOI : 10.1080/01621459.1963.10500845

C. Rozenblat, G. Melançon, and P. Koenig, Continental integration in multilevel approach of world air transportation Networks and Spatial Economics, 2000.

S. E. Schaeffer, Graph clustering, Computer Science Review, vol.1, issue.1, pp.27-64, 2007.
DOI : 10.1016/j.cosrev.2007.05.001

M. Steinbach, G. Karypis, and V. Kumar, A comparison of document clustering techniques, 2000.

S. Wasserman and K. Faust, Social Network Analysis: Methods and Applications, 1994.
DOI : 10.1017/CBO9780511815478