V. Abello, K. Ham, and B. Ackerman, ASK-GraphView: A Large Scale Graph Visualization System, Measures of Clustering Quality: A Working Set of Axioms for Clustering. Neural Information Processing Systems Conference (NIPS 2008) [3] Anonymized for blind review, pp.669-676, 2006.
DOI : 10.1109/TVCG.2006.120

C. Auber, J. , and M. , 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/hal-00307629

G. Blondel and L. Lambiotte, Fast unfolding of communities in large networks, Journal of Statistical Mechanics: Theory and Experiment, vol.2008, issue.10, p.10008, 2008.
DOI : 10.1088/1742-5468/2008/10/P10008
URL : https://hal.archives-ouvertes.fr/hal-01146070

F. Boutin, Filtrage, partitionnement et visualisation multi-échelles de graphes d'interactions à partir d'un focus: Experiments on Graph Clustering Algorithms, pp.568-579, 2003.

M. E. Clauset, C. Newman, and . Moore, Finding community structure in very large networks, Physical Review E, vol.70, issue.6, 2001.
DOI : 10.1103/PhysRevE.70.066111

G. Dhillon, Kulis: A fast kernel-based multilevel algorithm for graph clustering, KDD, pp.629-634, 2005.

. Freeman, A Set of Measures of Centrality Based on Betweenness, Sociometry, vol.40, issue.1, pp.35-41, 1977.
DOI : 10.2307/3033543

N. Girvan, Community structure in social and biological networks, Proc. Natl
DOI : 10.1073/pnas.122653799

T. R. Green, Cognitive dimensions of notations, pp.443-460, 1989.

D. A. Huffman, A method for the construction of minimum-redundancy codes, Proc. Inst
DOI : 10.1007/BF02837279

A. Inselberg and B. Dimsdale, Parallel coordinates: a tool for visualizing multi-dimensional geometry, Proceedings of the First IEEE Conference on Visualization: Visualization `90, pp.361-378, 1990.
DOI : 10.1109/VISUAL.1990.146402

. Jain, Data clustering: 50 years beyond K-means. Pattern Recogn, Lett, vol.31, issue.8, pp.651-666, 2010.

A. Karypis, . Kumar, and . Shekhar, Multilevel hypergraph partitioning, Proceedings of the 34th annual conference on Design automation conference , DAC '97, pp.526-529
DOI : 10.1145/266021.266273

G. Karypis and V. Kumar, A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs, SIAM Journal on Scientific Computing, vol.20, issue.1, p.359, 1999.
DOI : 10.1137/S1064827595287997

L. Kernighan, An Efficient Heuristic Procedure for Partitioning Graphs, Bell System Technical Journal, vol.49, issue.2, pp.291-308, 1970.
DOI : 10.1002/j.1538-7305.1970.tb01770.x

. Kleinberg, An Impossibility Theorem for Clustering, Advances in Neural Information Processing Systems (NIPS) 15, 2002.

M. Lafourcade, Making People Play for Lexical Acquisition with the JeuxDeMots prototype, SNLP 2007: 7th International Symposium on Natural Language Processing, 2007.
URL : https://hal.archives-ouvertes.fr/lirmm-00200883

A. Lewis and D. Sa, Human Cluster Evaluation and Formal Quality Measures, Proc. 34th Annual Conference of the Cognitive Science Society, 2012.

. Macqueen, Some methods of classification and analysis of multivariate observations, Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, 1967.

M. Mancoridis, . Rorres, . Chen, and . Gansner, Using automatic clustering to produce high-level system organizations of source code, Proceedings. 6th International Workshop on Program Comprehension. IWPC'98 (Cat. No.98TB100242), 1998.
DOI : 10.1109/WPC.1998.693283

. Newman, Finding community structure in networks using the eigenvectors of matrices, Physical Review E, vol.74, issue.3, p.36104, 2006.
DOI : 10.1103/PhysRevE.74.036104

. A. Noack, An Energy Model for Visual Graph Clustering, Proceedings of the 11th International Symposium on Graph Drawing, pp.425-436, 2003.
DOI : 10.1007/978-3-540-24595-7_40

L. Pons, Computing Communities in Large Networks Using Random Walks, Journal of Graph Algorithms and Applications, vol.10, issue.2, pp.191-218, 2006.
DOI : 10.7155/jgaa.00124

. Raghavan, Near linear time algorithm to detect community structures in large-scale networks, Physical Review E, vol.76, issue.3, 2007.
DOI : 10.1103/PhysRevE.76.036106

J. Reichardt and S. Bornholdt, Statistical mechanics of community detection, Physical Review E, vol.74, issue.1, p.16110, 2006.
DOI : 10.1103/PhysRevE.74.016110

B. Rosvall, Maps of random walks on complex networks reveal community structure, Proceedings of the National Academy of Sciences, pp.1118-1123, 2008.
DOI : 10.1073/pnas.0706851105

B. Salton, Term-weighting approaches in automatic text retrieval, Information Processing & Management, vol.24, issue.5, 1987.
DOI : 10.1016/0306-4573(88)90021-0

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

Y. Seberry, Hadamard matrices, sequences and block designs, Contemporary Design Theory:A Collection of Surveys, pp.431-560, 1992.

M. Shi, Normalized Cuts and Image Segmentation, Proceedings of the, 1997.

. Steinbach, . Karypis, and . Kumar, A comparison of document clustering techniques, KDD workshop on text mining, pp.525-526, 2000.

. Stijn-van-dongen, Graph Clustering by Flow Simulation, 2000.

Z. Wang and L. , Regularized clustering for documents, Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, SIGIR '07, pp.95-102, 2007.
DOI : 10.1145/1277741.1277760

W. Xu, Survey of Clustering Algorithms, IEEE Transactions on Neural Networks, vol.16, issue.3, pp.645-678, 2005.
DOI : 10.1109/TNN.2005.845141

S. Yu, Multiclass spectral clustering, Proceedings Ninth IEEE International Conference on Computer Vision, pp.313-319
DOI : 10.1109/ICCV.2003.1238361

B. Zadeh, A Uniqueness Theorem for Clustering, Uncertainty in Artificial Intelligence UAI, 2009.

K. Zhao, Criterion functions for document clustering: Experiments and analysis, 2001.