. V. Bbd-*-11-]-batagelj, . J. Brandenburg-f, . Didimo-w, . Liotta-g, . Palladino-p et al., Visual analysis of large graphs using (x, y)-clustering and hybrid visualizations, IEEE transactions on visualization and computer graphics, vol.17, pp.11-1587, 2011.

. M. Bbhr-*-16-]-behrisch, . Bach-b, . Henry-riche-n, and F. Schreck-t, Matrix Reordering Methods for Table and Network Visualization, Computer Graphics Forum, vol.35, issue.2, pp.24-27, 2016.

. A. Bezerianos, F. Dragicevic-p, . Bae-j, and . Watson-b, GeneaQuilts: A System for Exploring Large Genealogies, IEEE Transactions on Visualization and Computer Graphics, vol.16, issue.6, pp.1073-1081, 2010.
DOI : 10.1109/TVCG.2010.159
URL : https://hal.archives-ouvertes.fr/inria-00532939

. [. Gaertler-m and . Wagner-d, Experiments on graph clustering algorithms, 2003.

D. L. Menon-r, Openmp: an industry standard api for shared-memory programming, Computational Science & Engineering, vol.5, issue.1 8, pp.46-55, 1998.

D. M. and R. J. Mcguffin-m, Alertwheel: radial bipartite graph visualization applied to intrusion detection system alerts, IEEE Network, vol.26, issue.6 3, 2012.

R. [. Ramos-g and . Dumais-s, Pivotpaths: Strolling through faceted information spaces, IEEE Transactions on Visualization and Computer Graphics, vol.18, issue.12, pp.2709-2718, 2012.

. N. Edg-*-08-]-elmqvist, G. H. Do-t.-n, H. N. , and F. , Zame: Interactive large-scale graph visualization, Pacific Visualization Symposium (PacificVis), pp.215-222, 2008.

F. Primet-r, Progressive analytics: A computation paradigm for exploratory data analysis. arXiv preprint arXiv:1607, p.5162, 2016.

G. R. Gar09, Echo chambers online?: Politically motivated selective exposure among internet news users, Journal of Computer- Mediated Communication, vol.14, issue.9 10, pp.265-285, 2009.

. S. Ghani, L. C. Kwon-b, and Y. J. Elmqvist-n, Visual Analytics for Multimodal Social Network Analysis: A Design Study with Social Scientists, IEEE Transactions on Visualization and Computer Graphics, vol.19, issue.12, pp.12-2032, 2013.
DOI : 10.1109/TVCG.2013.223

H. N. and F. J. Mcguffin-m, Nodetrix: a hybrid visualization of social networks, pp.1302-1309, 2007.

[. I. Herman and M. M. Melançon-g, Graph visualization and navigation in information visualization: A survey, IEEE Transactions on Visualization and Computer Graphics, vol.6, issue.1, pp.24-43, 2000.
DOI : 10.1109/2945.841119

]. Hol06 and . D. Holten, Hierarchical edge bundles: Visualization of adjacency relations in hierarchical data, IEEE Transactions on Visualization and Computer Graphics, vol.12, issue.5, pp.741-748, 2006.

H. T. Pezzotti-n, . Van-unen-v, . Koning-f, . P. Lelieveldt-b, and . Vilanova-a, Cyteguide: Visual guidance for hierarchical single-cell analysis, IEEE Transactions on Visualization and Computer Graphics, vol.24, issue.10, 2017.

H. J. Hsbw11-], . Seifert-r, and W. D. Burch-m, Bicluster viewer: a visualization tool for analyzing gene expression data, Advances in Visual Computing, pp.641-652, 2011.

[. S. Schumann-h and S. , A survey of multi-faceted graph visualization, Eurographics Conference on Visualization (EuroVis). (2015), pp.1-20

H. D. Van and W. J. , Force-directed edge bundling for graph visualization, In Computer Graphics Forum, vol.28, pp.983-990, 2009.

L. B. Plaisant-c, F. Sims-c, and H. N. , Task taxonomy for graph visualization URL: https, BELIV '06: Proceedings of the 2006 AVI workshop on BEyond time and errors, pp.1-5, 2006.

L. , L. D. Ssi-yan-, and K. G. Kaser-o, Consistently faster and smaller compressed bitmaps with roaring. Software: Practice and Experience, pp.1547-1569, 2016.

A. M. Mah-*-12-]-martins-r, P. F. Heberle-h, P. H. De-andrade-lopes-a, and . Minghim-r, Multidimensional Projections for Visual Analysis of Social Networks, Journal of Computer Science and Technology, vol.20, issue.9, pp.791-810, 2012.
DOI : 10.1080/03610929108830679

M. Y. , C. S. Zhang-r, L. Z. , C. Y. , and S. Y. Qu-h, Understanding hidden memories of recurrent neural networks. arXiv preprint arXiv, pp.1710-10777, 2017.

[. Hatcher-e and . Gospodnetic-o, Lucene in Action: Covers Apache Lucene 3.0, 2010.

M. M. Lowe-d, Scalable nearest neighbor algorithms for high dimensional data, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.36, issue.6, pp.2227-2240, 2014.

M. S. Oliveira-a, Biclustering algorithms for biological data analysis: a survey, IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), vol.1, issue.2, pp.24-45, 2004.

P. T. Mpg-*-14-]-mühlbacher, G. S. Sedlmair-m, and . Streit-m, Opening the black box: Strategies for increased user involvement in existing algorithm implementations, IEEE Transactions on Visualization and Computer Graphics, vol.20, issue.8, pp.12-1643, 2014.

. A. Oghabian, H. S. Kilpinen-s, and C. E. , Biclustering Methods: Biological Relevance and Application in Gene Expression Analysis, PLoS ONE, vol.4, issue.3, p.3, 2014.
DOI : 10.1371/journal.pone.0090801.t004

[. Giráldez-r and . S. Aguilar-ruiz-j, High dimensional inspector URL: https://github.com/Nicola17 Biclustering on expression data: A review, Journal of biomedical informatics, vol.6, issue.2, pp.163-180, 2015.

. N. Phl-*-16-]-pezzotti, . Höllt-t, . Lelieveldt-b, . Eisemann-e, and . Vilanova-a, Hierarchical Stochastic Neighbor Embedding, Computer Graphics Forum, vol.11, issue.2579, pp.21-30, 2016.
DOI : 10.1109/INFVIS.2004.60

P. N. Lelieveldt-b, . L. Van-der-maaten, . Hollt-t, . Eisemann-e, and . Vilanova-a, Approximated and user steerable tsne for progressive visual analytics, IEEE Transactions on Visualization and Computer Graphics PP, pp.99-100, 2016.

R. A. Cherry-c, Results of a prototype television bandwidth compression scheme, Proceedings of the IEEE, vol.55, issue.4, pp.356-364, 1967.

S. J. Görg-c and . Liu-z, Jigsaw: supporting investigative analysis through interactive visualization, Information visualization, vol.7, issue.2, pp.118-132, 2008.

. [. Liu-j and M. Q. Zhang-m, Visualizing largescale and high-dimensional data, Proceedings of the 25th International Conference on World Wide Web, pp.287-297, 2016.

. L. Van-der-maaten and . Hinton-g, Visualizing data using t-SNE, Journal of Machine Learning Research, vol.9, issue.2, pp.2579-2605, 2008.

K. T. Von, K. J. Schreck-t, W. J. Van, F. , and F. D. , Visual analysis of large graphs: state-of-the-art and future research challenges, In Computer Graphics Forum, vol.30, issue.2 3, pp.1719-1749, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00712779

X. P. Cao-n, . Qu-h, and . J. Stasko, Interactive visual cocluster analysis of bipartite graphs, Pacific Visualization Symposium (PacificVis), pp.32-39, 2016.

. M. Zxw-*-16-]-zaharia, W. S. Xin-r, . Das-t, D. M. Arm-brust, R. J. Meng-x et al., Apache spark: A unified engine for big data processing, Communications of the ACM, vol.59, pp.11-56, 2016.

[. Xu-p, . Yuan-x, and . Qu-h, Edge bundling in information visualization, Tsinghua Science and Technology, vol.18, issue.2, pp.145-156, 2013.