R. Agrawal, T. Imielinski, and A. Swami, Mining association rules between sets of items in large databases, Proc. of the 1993 ACM SIGMOD international conference on management of data, pp.207-216, 1993.

R. Agrawal and R. Srikant, Fast algorithms for mining association rules, Proc. of the 20th international conference on very large data bases (VLDB), pp.487-499, 1994.

J. Barthelemy and E. Mullet, A model of selection by aspects, Acta Psychologica, vol.79, issue.1, pp.1-19, 1992.
DOI : 10.1016/0001-6918(91)90070-G

I. Bhandari, Attribute Focusing: machine-assisted knowledge discovery applied to software production process control, Knowledge Acquisition, vol.6, issue.3, pp.271-294, 1994.
DOI : 10.1006/knac.1994.1014

J. Blanchard, F. Guillet, and H. Briand, A user-driven and quality-oriented visualization for mining association rules, Third IEEE International Conference on Data Mining, pp.493-496, 2003.
DOI : 10.1109/ICDM.2003.1250960
URL : https://hal.archives-ouvertes.fr/hal-00461397

J. Blanchard, P. Kuntz, F. Guillet, and R. Gras, Implication Intensity, Statistical data mining and knowledge discovery, pp.473-485, 2003.
DOI : 10.1201/9780203497159.ch28
URL : https://hal.archives-ouvertes.fr/hal-00420993

M. Botta, J. F. Boulicaut, C. Masson, and R. Meo, A Comparison between Query Languages for the Extraction of Association Rules, Proc. of the 4th international conference on data warehousing and knowlege discovery, pp.1-10, 2002.
DOI : 10.1007/3-540-46145-0_1

J. R. Brachman, A. , and T. , The process of knowledge discovery in databases: a human-centered approach Advances in knowledge discovery and data mining, pp.37-58, 1996.

D. Braga, A. Campi, M. Klemettinen, and L. P. , Mining Association Rules from XML Data, Proc. of the 4th international conference on data warehousing and knowlege discovery, pp.21-30, 2002.
DOI : 10.1007/3-540-46145-0_3

W. Buntine, Graphical models for discovering knowledge Advances in knowledge discovery and data mining, pp.59-82, 1996.

S. K. Card, J. D. Mackinlay, and B. Schneiderman, Readings in Information Visualization: Using vision to think, 1999.

C. M. Carswell, S. Frankenberger, and B. D. , Graphing in depth: perspectives on the use of three-dimensional graphs to represent lower-dimensional data, Behaviour & Information Technology, vol.2, issue.6, pp.459-474, 1991.
DOI : 10.1037/0096-1523.16.4.683

C. Chen, W. S. Cleveland, and R. Mcgill, Information Visualization: beyond the horizon Graphical perception: theory, experimentation, and application to the development of graphical methods, Journal of the American Statistical Association, vol.79, pp.387-531, 1984.

W. S. Cleveland, W. Lai, K. Misue, and K. Sugiyama, The elements of graphing data Preserving the mental map of a diagram, Proc. of Compugraphics, pp.24-33, 1985.

U. M. Fayyad, G. G. Grinstein, and W. A. , Information visualization in data mining and knowledge discovery, 2001.

W. J. Frawley, G. Piatetsky-shapiro, and C. J. Matheus, Knowledge Discovery in Databases: an overview, Knowledge Discovery in Databases, AAAI, pp.1-30, 1991.

P. Fule and J. F. Roddick, Experiences in building a tool for navigating association rule result sets, CRPIT'04: Proc. of the second Australasian workshop on data mining and web intelligence, pp.103-108, 2004.

G. W. Furnas, Generalized fisheye views, CHI'86: Proceedings of the SIGCHI conference on Human factors in computing systems, pp.16-23, 1986.
DOI : 10.1145/22339.22342

R. Gras, L'implication statistique : nouvelle méthode exploratoire de données, La Pensée Sauvage Editions, 1996.

G. G. Grinstein, Harnessing the human in knowledge discovery, Proc. of the 2nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp.384-385, 1996.

H. Hamilton and F. Guillet, Quality Measures for Data Mining, 2006.

J. Han, Y. Fu, W. Wang, K. Koperski, and O. Zaiane, DMQL: a data mining query language for relational databases, Proc. of the 1996 SIGMOD workshop on research issues on data mining and knowledge discovery, 1996.

J. Han, J. Y. Chiang, S. Chee, J. Chen, Q. Chen et al., DBMiner: A system for data mining in relational databases and data warehouses, Proc. of CASCON'97: Meeting of Minds, pp.249-260, 1997.

M. C. Hao, U. Dayal, M. Hsu, T. Sprenger, and M. H. Gross, Visualization of directed associations in e-commerce transaction data, Proc. of VisSym, pp.185-192, 2001.
DOI : 10.1007/978-3-7091-6215-6_20

J. Hipp, U. Gntzer, and G. Nakhaeizadeh, Algorithms for association rule mining --- a general survey and comparison, ACM SIGKDD Explorations Newsletter, vol.2, issue.1, pp.58-64, 2000.
DOI : 10.1145/360402.360421

H. Hofmann, A. P. Siebes, and W. A. , Visualizing association rules with interactive mosaic plots, Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '00, pp.227-235, 2000.
DOI : 10.1145/347090.347133

H. Hofmann and A. Wilhelm, Visual Comparison of Association Rules, Computational Statistics, vol.16, issue.3, pp.399-415, 2001.
DOI : 10.1007/s001800100075

P. Horschka and W. Klsgen, A support system for interpreting statistical data, 1991.

T. Imielinski and H. Mannila, A database perspective on knowledge discovery, Communications of the ACM, vol.39, issue.11, pp.58-64, 1996.
DOI : 10.1145/240455.240472

T. Imielinski and A. Virmani, MSQL: A query language for database mining, Data Mining and Knowledge Discovery, vol.3, issue.4, pp.373-408, 1999.
DOI : 10.1023/A:1009816913055

B. Jeudy and J. Boulicaut, Optimization of association rule mining queries. Intelligent Data Analysis, pp.341-357, 2002.

D. A. Keim and H. Kriegel, Visualization techniques for mining large databases: a comparison, IEEE Transactions on Knowledge and Data Engineering, vol.8, issue.6, pp.923-938, 1996.
DOI : 10.1109/69.553159

M. Klemettinen, H. Mannila, P. Ronkainen, H. Toivonen, and A. I. Verkamo, Finding interesting rules from large sets of discovered association rules, Proceedings of the third international conference on Information and knowledge management , CIKM '94, pp.401-407, 1994.
DOI : 10.1145/191246.191314

P. Kuntz, F. Guillet, R. Lehn, and H. Briand, A User-Driven Process for Mining Association Rules, Proc. of the 4th European conference on principles of data mining and knowledge discovery (PKDD-2000), pp.483-489, 2000.
DOI : 10.1007/3-540-45372-5_55

P. Kuntz, R. Lehn, and H. Briand, Dynamic rule graph drawing by genetic search, SMC 2000 Conference Proceedings. 2000 IEEE International Conference on Systems, Man and Cybernetics. 'Cybernetics Evolving to Systems, Humans, Organizations, and their Complex Interactions' (Cat. No.00CH37166), pp.45-58, 2000.
DOI : 10.1109/ICSMC.2000.884365

J. Lamping, R. Rao, and P. Pirolli, A focus+context technique based on hyperbolic geometry for visualizing large hierarchies, Proceedings of the SIGCHI conference on Human factors in computing systems, CHI '95, pp.401-408, 1995.
DOI : 10.1145/223904.223956

R. Lehn, An interactive rule visualization system for knowledge discovery in databases, 2000.

Y. Ma, B. Liu, and C. K. Wong, Web for data mining, ACM SIGKDD Explorations Newsletter, vol.2, issue.1, pp.16-23, 2000.
DOI : 10.1145/360402.360408

R. Meo, G. Psaila, and C. S. , An extension to SQL for mining association rules, Data Mining and Knowledge Discovery, vol.2, issue.2, pp.195-224, 1998.
DOI : 10.1023/A:1009774406717

H. Montgomery, Decision rules and the search for a dominance structure: towards a process model of decision making Analysing and aiding decision processes, pp.343-369, 1983.

R. T. Ng, L. V. Lakshmanan, J. Han, and A. Pang, Exploratory mining and pruning optimizations of constrained associations rules, Proc. of the 1998 ACM SIGMOD international conference on management of data, pp.13-24, 1998.

B. Pinaud, P. Kuntz, and R. Lehn, Dynamic Graph Drawing with a Hybridized Genetic Algorithm, Proc. of Automatic Computing in Design and Manufacture VI, pp.365-375, 2004.
DOI : 10.1007/978-0-85729-338-1_31
URL : https://hal.archives-ouvertes.fr/inria-00335944

H. Purchase, Which aesthetic has the greatest effect on human understanding?, Proc. of Graph Drawing'97, pp.248-261, 1997.
DOI : 10.1007/3-540-63938-1_67

C. P. Rainsford and J. F. Roddick, Visualisation of Temporal Interval Association Rules, 2000.
DOI : 10.1007/3-540-44491-2_14

G. Robertson, M. Czerwinski, K. Larson, D. C. Robbins, D. Thiel et al., Data mountain, Proceedings of the 11th annual ACM symposium on User interface software and technology , UIST '98, pp.153-162, 1998.
DOI : 10.1145/288392.288596

M. Sarkar and M. H. Brown, Graphical fisheye views of graphs, Proceedings of the SIGCHI conference on Human factors in computing systems , CHI '92, pp.83-91, 1992.
DOI : 10.1145/142750.142763

B. Shneiderman, The Eyes Have It: a task by data type taxonomy for information visualization, Proceedings of IEEE Symposium on Visual Languages VL'96, pp.336-343, 1996.

H. A. Simon, Models of Thought, 1979.

I. Spence, Visual psychophysics of simple graphical elements., Journal of Experimental Psychology: Human Perception and Performance, vol.16, issue.4, pp.683-692, 1990.
DOI : 10.1037/0096-1523.16.4.683

R. Spence, Information Visualization The Visual Display of Quantitative Information Exploratory data analysis, Graphics Press Tukey J.W, 1977.

A. Tuzhilin and G. Adomavicius, Handling very large numbers of association rules in the analysis of microarray data, Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '02, pp.396-404, 2002.
DOI : 10.1145/775047.775104

A. R. Unwin, H. Hofmann, and K. Bernt, The TwoKey Plot for Multiple Association Rules Control, Proc. of 5th European conference on principle and practice of knowledge discovery in databases (PKDD'01), pp.472-483, 2001.
DOI : 10.1007/3-540-44794-6_39

P. C. Wong, P. Whitney, and T. J. , Visualizing association rules for text mining, Proc. of the 1999 IEEE symposium on information visualization, pp.120-123, 1999.