Références

  1. [Aamodt et Plaza, 1994] Aamodt A., Plaza E.: Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches. Artificial Intelligence Communications. IOS Press, vol. 7(1), pp. 39-59, 1994.
  2. [AFNOR, 2003] AFNOR : Ergonomie de l’informatique. Aspects logiciels, matériels et environnementaux, Recueil Normes Informatique, ISBN 2-12-236211-1, 2003.
  3. [Aha et Kibler, 1991]Aha D., Kibler D.: Instance-based learning algorithms, Machine Learning, vol.6, pp.37-66, 1991.
  4. [Ankerst et al, 1999] Ankerst M., Elsen C., Ester M., Kriegel H.-P.: Visual classification: An interactive approach to decision tree construction. In Proc. of the Fifth International Conference on Knowledge Discovery and Data Mining, pp.392–396, 1999.
  5. [Ankerst et Keim, 1996] Ankerst M., Keim D.A., Kriege H-P.: 'Circle Segments': A Technique for Visually Exploring Large Multidimensional Data Sets. In Proc. Of Visualization'96, Hot Topic Session, 1996.
  6. [Ankerst, 2000] Ankerst M.: Visual Data Mining. PhD Thesis, Ludwig Maximilians University of Munich, 2000.
  7. [AS Evaluation, 2005] http://www.lirmm.fr/InfoViz/ASEval/index.php, accédé le 21 septembre 2005.
  8. [Asimov, 1985] Asimov D.: The grand tour: A tool for viewing multidimensional data. SIAM Journal on Scientific and Statistical Computing, vol. 6(1), pp.128-143, January 1985.
  9. [Atkerson et al., 1997] Atkeson C., Moore A., Schaal S.: Locally weighted learning, Artificial Intelligence Review, vol.11, pp.11-73, 1997.
  10. [Bach, 2004] Bach C. : Elaboration et validation de Critères Ergonomiques pour les Interactions Homme-Environnements Virtuels, Thèse de doctorat, Université de METZ, 2004.[Balbo, 1994] Balbo S. : Evaluation ergonomique des interfaces utilisateur : un pas vers l'automatisation, Thèse préparée au sein du Laboratoire de Génie Informatique - IMAG - Genoble1, 1994.
  11. [Barthélemy et al, 1984] Barthélemy J.-P., Leclerc B., Monjardet B., 1984 : Quelques aspects du consensus en classification, in Dara analysis and informatics (eds. Diday et al.), Amsterdam: Elsevier, pp.307-315, 1984.
  12. [Barthélemy et Janowitz, 1991] Barthélemy J.-P., Janowitz M.F.: A formal theory of consensus, Siam. J. Discr. Math., vol. 4, pp.305-322, 1991.
  13. [Barthet, 1988] Barthet M.F. : Logiciels interactifs et ergonomie, modèles et méthodes de conception, Dunod Informatique, 219 pages, 1988.
  14. [Basili et al, 1994] Basili V., Caldiera G., Rombach D.: The Goal Question Metric Approach. Encyclopedia of Software Engineering, Wiley 1994.
  15. [Bastien et Scapin, 1993] Bastien J.M.C., Scapin D.L. : Critères ergonomiques pour l’évaluation d’interfaces utilisateurs. Rapport technique INRIA n° 156, Juin 1993, INRIA : Le Chesnay, 1993.
  16. [Bastien et Scapin, 1993b] Bastien J.M., Scapin D.L.: Preliminary Findings on the Effectiveness of Ergonomic Criteria for the Evaluation of Human-Computer Interfaces, in Proceedings of INTERCHI’93. pp.187-188, 1993.
  17. [Bertin, 1967] Bertin J. : La Sémiologie graphique Paris, Mouton, 1967.
  18. [Bertin, 1977] Bertin J. : La Graphique et le traitement Graphique de l'information. Flammarion, 1977.
  19. [Bertin, 1981] Bertin J.: Graphics And Graphic Information-Processing. Berlin. Walter de Gruyter, 1981.
  20. [Bisson, 2000] Bisson G. : La similarité : une notion symbolique/numérique. Apprentissage symbolique-numérique (tome 2). Eds Moulet, Brito. Editions CEPADUES. pp.169-201, 2000.
  21. [Blake et Merz, 1998] Blake C., Merz C.: UCI Repository of machine learning databases, [www.ics.uci.edu/~mlearn/MLRepository.html]. Irvine, University of California, Department of Information and Computer Science, 1998.
  22. [Boehm et Basili, 2001] Boehm B. et Basili V.: Software Defect Reduction Top 10 List, IEEE Computer, Vol.. 34, No. 1, January 2001.
  23. [Boëhm, 1978] Boëhm B.: Characteristics of software quality, Vol 1 of TRW series on software technology, North-Holland, Amsterdam, Netherlands, 1978.
  24. [Brazdil et al., 2003] Brazdil P., Soares C., Costa J.: Ranking Learning Algorithms Machine Learning: Using IBL and Meta-Learning on Accuracy and Time Results. Machine Learning, vol. 50(3), pp.251-277, 2003.
  25. [Brazdil et Soares, 2000] Brazdil P., Soares C.: A Comparison of Ranking Methods for Classification Algorithm Selection, Machine Learning: ECML 2000,  11th European Conference on Machine Learning, R. López de Mántaras and E. Plaza (Eds.), LNAI 1810, Springer Verlag, pp.63-74, 2000.
  26. [Brodley, 1995] Brodley C.: Recursive Automatic Bias Selection for Classifier Construction. Machine Learning, vol. 20(1-2), pp.63-94, 1995.
  27. [Brown, 1988] Brown C.M.L.: Human-Computer Interface Design Guidelines, Xerox Corporation, 1988.
  28. [Brunk et al., 1997] Brunk C., Kelly J. Kohavi R.: MineSet : an integrated system for data mining, International Conference on Knowledge Discovery and Data Mining (KDD’97), AAAI Press, pp 135-138, 1997.
  29. [Calvary, 2002] Calvary G. : Ingénierie de l'interaction homme-machine : rétrospective et perspectives, Interaction homme-machine et recherche d'information, Traité des Sciences et Techniques de l'Information, Lavoisier, Hermès, pp.19-63, 2002.
  30. [Card et al, 1999] Card S., Mackinlay, J., Scneiderman B.: Readings in Information Visualization: Using Vision to Think, Morgan Kaufman, 1999.
  31. [Card et Mackinlay, 1997] Card S. K., Mackinlay J.:The structure of the information visualization design space. In Proceedings of the IEEE Symposium on Information Visualization 1997 (InfoVis 1997), pp. 92-99, 1997.
  32. [Chambers et al, 1983] Chambers J., Cleveland W., Kleiner B., Tukey P.: Graphical Methods for Data Analysis, Wadsworth, 1983.
  33. [Chandrasekaran et al., 1992] Chandrasekaran B., Johnson T.R., Smith, J.W.: Task-Structure Analysis for Knowledge Modeling. CACM 35, vol. 9, pp.124-137, 1992.
  34. [Chen et al., 2005] Chen Y., Chu C.-H., Mullen T., Pennock D. M.: Information Markets vs. Opinion Pools: An Empirical Comparison , ACM Conference on Electronic Commerce (EC 05), Vancouver, British Columbia, Canada, June 5-8, pp.58-67, 2005.
  35. [Chen et Czerwinski, 2000] Chen C., Czerwinski M.: Empirical evaluation of Information Visualizations: an introduction”, International Journal of Human-Computer Studies, Vol. 53, pp.631-635, 2000.
  36. [Chernoff, 1973] Chernoff H.: The use of faces to represent points in k-dimensional space graphically. Journal of the American Statistical Association, vol. 68, pp.361-368, 1973.
  37. [Chi, 2000] Chi Ed H.: A Taxonomy of Visualization Techniques using the Data State Reference Model. In Proceedings of the Symposium on Information Visualization (InfoVis '00), IEEE Press, 2000. Salt Lake City, Utah, pp.69-75, 2000.
  38. [Cleary et Trigg, 1995] Cleary J.G., Trigg L.E.: K*: An Instance- based Learner Using an Entropic Distance Measure, Proceedings of the 12th International Conference on Machine learning, pp.108-114, 1995.
  39. [Clemen et Winkler, 1999] Clemen R. T., Winkler, R. L.: Combining probability distributions from experts in risk analysis. Risk Analysis, vol.19(2), pp.187–203, 1999.
  40. [Cohen, 1995] Cohen W.W.: Fast Effective Rule Induction in Proceedings of the Twelfth International Conference on Machine Learning, pp.115-123, 1995.
  41. [Collier et al., 1999] Collier K., Carey B., Sautter D., Marjaniemi C.: A Methodology for Evaluating and Selecting Data Mining Software. In proc of the 32nd Hawaii International Conference on System Sciences, 1999.
  42. [Constantine, 2001] Constantine L.L.: Design studies 1-3. http://foruse.com/Resources.htm#Articles, 2001, accédé en mars 2005.
  43. [Cook, 1991] Cook R. M.: Experts in Uncertainty: Opinion and Subjective Probability in Science. Oxford University Press, New York, 1991.
  44. [Costabile, 2001] Costabile M.F.: Usability in software life cycle In Handbook of of Software Engineering and Knowledge Engineering, SK Chang Ed., World Scientific, Vol , World Scientific Publ. Company, pp.179-192, 2001.
  45. [Coutaz et al., 1993] Coutaz J., Salber D., Balbo S.: Towards Automatic Evaluation of Multimodal User Interfaces, Amodeus Project document : SM/WP32, 1993.
  46. [Coutaz, 1990] Coutaz J. : Interfaces homme-ordinateur : Conception et Réalisation. Bordas, Paris, 1990.
  47. [Cox et al, 1997] Cox K.C., Eick S.G., Wills G.J., Brachman R.J.: Visual Data Mining: Recognizing Telephone Calling Fraud, Fraud, Data Mining and Knowledge Discovery Vol. 1, pp.225-231, 1997.
  48. [Crampes, 1995] Crampes M. : Composition Multimédia dans un Contexte Narratif. Thèse de doctorat de l'Université de Montpellier II - Sciences et Techniques du Languedoc, 1995.
  49. [Day et McMorris, 2003] Day W.H.E., McMorris F.R.: Axiomatic Consensus Theory in Group Choice and Biomathematics, SIAM, Philadelphia, 2003.
  50. [Detweiler et Omanson, 1996] Detweiler M.C., Omanson R.C.: Ameritech Web Page User Interface Standards and DesignGuidelines, Ameritech Corp., Chicago, 1996. Accessible at http://www.ameritech.com/corporate/testtown/library/standard/web_guidelines/index.html
  51. [Dix et al., 1998] Dix A., Finlay J., Abowd G., Beale R.: Human-Computer Interaction, Second Edition, Prentice Hall, 1998.
  52. [Do et Poulet, 2005] Do T-N., Poulet, F.: Mining Very Large Datasets with SVM and Visualization ", in proc. of ICEIS'05, 7th Int. Conf. on Entreprise Information Systems, Miami, USA, 2005, Vol. 2, pp.127-141, 2005.
  53. [Domenach et Leclerc, 2004] Domenach F., Leclerc B.: “ Consensus of classification systems, with Adams' results revisited ”. In D. Banks, L. House, F.R. McMorris, P. Arabie, and W. Gaul, editors, Classification, Clustering and Data Mining Applications, Springer, Berlin, pp.417-428, 2004.
  54. [Domingos et Hulten, 2001] Domingos P., Hulten G.: Catching Up with the Data: Research Issues in Mining Data Streams. Proceedings of the Workshop on Data Mining and Knowledge Discovery, ACM SIGMOD/PODS’01, California, USA, 2001.
  55. [Dubuisson, 1990] Dubuisson B. : Diagnostic et reconnaissance des formes, Hermès, 1990.
  56. [Dull et Tegarden, 1999] Dull R.B., Tegarden D.P.: A comparison of three visual representations of complex multidimensional accounting information. Journal of Information Systems. Vol. 13, No. 2 (Fall), pp. 117-131, 1999.
  57. [Dumas, 1999] Dumas J., Redish J.: A Practical Guide to Usability Testing. Intellect Books, Portland, OR, 1999 (revised edition).
  58. [Eibe et Witten, 1998] Eibe F., Witten I. H.: Generating Accurate Rule Sets Without Global Optimization. In Shavlik, J. ed., Machine Learning: Proceedings of the Fifteenth International Conference, San Francisco, CA, Morgan Kaufmann Publishers, 1998.
  59. [Engels et Theusinger, 1998] Engels R., Theusinger C.: Using a Data Metric for Offering Preprocessing Advice in Data-mining Applications. In Proceedings of the Thirteenth European Conference on Artificial Intelligence, pp.430-434 1998.
  60. [Engels, 1996] Engels R.: Planning Tasks for Knowledge Discovery in Databases; Performing Task-Oriented User-Guidance. KDD 1996pp.170-175, 1996.
  61. [Fangseu Badjio et Poulet, 2004a] Fangseu Badjio E., Poulet F. : Guidage des utilisateurs en fouille visuelle de données, in proc. of EGC'04 Workshop on Visualization and Knowledge Discovery, Clermont-Ferrand, pp.13-18, 2004.
  62. [Fangseu Badjio et Poulet, 2005a] Fangseu Badjio E., Poulet F. : Définition des spécificités de la fouille visuelle des données pour une évaluation de l’interaction homme machine, in proc. of 3e Atelier Visualisation et Extraction de Connaissances, EGC'05, Paris, 2005, pp.7-14, 2005.
  63. [Fangseu Badjio et Poulet, 2005b] Fangseu Badjio E., Poulet F.: Dimension Reduction for Visual Data Mining, in proc. of ASMDA'05, the International Symposium on Applied Stochastic Models and Data Analysis, J. Janssen and P. Lenca (Eds), Brest, France, May 2005, pp.266- 275, 2005.
  64. [Fangseu Badjio et Poulet, 2005c] Fangseu Badjio E., Poulet F.: Visual data mining tools: quality metrics definition and application, in proc. of ICEIS'05, the 6th International Conference on Enterprise Information Systems, Miami, Florida, USA, May 2005, pp.98-103, 2005.
  65. [Fangseu Badjio et Poulet, 2005d] Fangseu Badjio E., Poulet F.: Ergonomic Criteria for Visual Data Mining, International Symposium of Visual Data Mining (VDM) of IEEE 9th International Conference on Information Visualization (IV@VDM'05), Poster, London, UK, Jul 2005 (accepted).
  66. [Fangseu Badjio et Poulet, 2005e] Fangseu Badjio E., Poulet F.: Towards usable visual data mining environments, to appear in proc. of HCII’05, the 11th International Conference on Human-Computer Interaction, Las Vegas, Nevada, USA, Jul 2005.
  67. [Fangseu Badjio et Poulet, 2005f] Fangseu Badjio E., Poulet F.: User Guidance: From Theory to Practice, the Case of Visual Data Mining, to appear in proc. of IEEE-ICTAI’05, the 17th IEEE International Conference on Tools with Artificial Intelligence, Hong Kong, China, Nov 2005.
  68. [Fangseu Badjio, 2005a] Fangseu Badjio E.: Quality evaluation of visual data mining tools, in proc. of AC'05, the IADIS International Conference Applied Computing 2005 - 22-25 February 2005, pp.133-138, 2005.
  69. [Farenc, 1997] Farenc C. : ERGOVAL : une méthode de structuration des règles ergonomiques permettant l'évaluation automatique d'interfaces graphique, Thèse de Doctorat de l'Université Toulouse 1, janvier 1997.
  70. [Fayyad et al., 1996] Fayyad, U. M., Piatetsky-Shapiro, G., Smyth, P.: editors Advances in Knowledge Discovery and Data Mining. AAAI Press / MIT Press, Menlo Park, CA, 1996.
  71. [Fayyad et Uthurusamy, 2002] Fayyad U., Uthurusamy R.: Evolving Data Mining into Solutions for Insights. Communication of the ACM, 45 (8), pp.28-31, 2002.
  72. [Ferber, 1995] Ferber J. : Les systèmes multi-agents. Vers une intelligence collective. InterEditions, Paris, 1995.
  73. [Fernandes, 1995] Fernandes T.: Global interface design: A guide to designing international user interfaces. Boston, MA: AP Professional, 1995.
  74. [Finyan et Huiqing, 2002] Jinyan L., Huiqing L.: Kent Ridge Bio-medical Data Set Repository. http://sdmc.lit.org.sg/GEDatasets, 2002, accédé le 2 octobre 2005..
  75. [Flanagan, 1954] Flanagan J. C.: The critical incident technique. Psychological Bulletin, vol. 51(4), pp.327-359, 1954.
  76. [French, 1985] French S.: Group consensus probability distributions: a critical survey. Bayesian Statistics, vol. 2, pp.83–202, 1985.
  77. [Freund et Schapire, 1996] Freund Y., Schapire R.E.: Experiments with a new boosting algorithm, in Proceedings of the International Conference on Machine Learning, Morgan Kaufmann, San Francisco, pp 148-156, 1996.
  78. [Furnas, 1986] Furnas G.W.: Generalized fisheye views. In Human Factors in Computing Systems CHI'86 Conference Proceedings, Boston, MA, pp.16-23, 1986.
  79. [Galitz, 1996] Galitz, W. O.: The essential guide to user interface design: An introduction to GUI design principles and techniques. New York: Wiley, 1996.
  80. [Genest et Zidek, 1986] Genest C., Zidek J. V.: Combining probability distributions: A critique and an annotated bibliography. Statistical Science, 1(1):114–148, 1986.
  81. [Ghezzi et al,. 1991] Ghezzi G., Jazayeri M., Mandrioli D.: Fundamentals of software engineering. Prentice-Hall, New Jersey, USA, 1991.
  82. [Google, 2005] GOOGLE: http://www.google.angel-cage.de/html/newsstatistics0704.html, 2005, accédé en mars 2005.
  83. [Gould et Lewis, 1985] Gould J.D., Lewis C. H., "Designing for Usability - Key Principles and What Designers Think," Communications of the ACM, 28, pp. 300-311, 1985.
  84. [Grinstein et al, 1997] Grinstein G.G., Hoffman P., Laskowski S.J, Pickett R.M.: Benchmark Development for the Evaluation of Visualization for Data Mining. In Proceedings of the Workshop: Issues in the Integration of Data Mining and Data Visualization, Newport Beach, California, 1997.
  85. [Hall, 2000] Hall M.: Correlation-based feature selection for discrete and numeric class machine learning. Proceedings of the Seventeenth International Conference on Machine Learning, pp. 359-366, 2000.
  86. [Han et Cercone, 2001] Han J., Cercone N.: "Interactive Construction of Decision Trees" in proc. of PAKDD'2001, LNAI 2035, pp.575-580, 2001.
  87. [Han et Kamber, 2001] Han J., Kamber M.: Data Mining: Concepts and Techniques. Morgan Kaufman, 2001.
  88. [Harinarayan et al., 1996] Harinarayan V., Rajaraman A., Ullman J.: Implementing Data Cubes Efficiently, Proc. ACM SIGMOD Conf, Montreal, pp.205-216, 1996.
  89. [Hatcheut et al., 2005] Hatchuet A., Masson P. L. & Weil B. (2005 à paraître), Activité de conception, organisation de l'entreprise et innovation, G. Minguet and C. Thuderoz, Eds.
  90. [Healey, 1996] Healey C.G.: Choosing Effective Colours for Data Visualization. In Proceedings of the 7th conference on Visualization '96, pp.263-270, 1996.
  91. [Hoc, 1991] Hoc J-M.: Book Review: ``Handbook of Human-Computer Interaction, '' edited by M. Helander. International Journal of Man-Machine Studies 35(6): 930-931,1991.
  92. [Holte, 1993] Holte R.C.: Very simple classification rules perform well on most commonly used datasets. Machine Learning, Vol. 11, pp.63-91, 1993.
  93. [Howard, 1987] Howard S., Murray D.: A taxonomy of evaluation techniques for HCI, in Proceedings of INTERACT’87, H.J.Bullinger and Shackel (Editors), Elsevier Science Publishers B.V. (North-Holland), IFIP, pp. 453-459, 1987.
  94. [Hû et al., 2001] Hû O., Trigano P., Crozat S. : Une aide à l’évaluation des logiciels Multimédias de formation, publié dans la revue STE - Sciences et Techniques Educatives (ed Hermès), numéro spécial ‘Communication Homme/Machine et Apprentissage’, Volume 8 n°3, pp.239-274, 2001.
  95. [Huber, 1985] Huber P.J.: Projection Pursuit, The Annals of Statistics, vol. 13 (2) pp. 435-474, 1985.
  96. [IEEE 610.12, 1990] ANSI/IEEE 610.12:1990: Glossary of software engineering terminology, 1990.
  97. [IMS-LIP, 2003] IMS Global Learning Consortium (2003a) IMS Learning Design Best Practice, Version 1.0 Final Specification, 138 p.; IMS Learning Design XML Binding, Version 1.0 Final Specification, 82 p.; IMS Learning Design Information Model, Version 1.0 Final Specification, 87 p.
  98. [Inselberg, 1985] Inselberg A.: The plane with parallel coordinates. The Visual Computer, vol. 1, pp.69-91, 1985.
  99. [Inselberg, 1998] Inselberg A.: Visual Data Mining with Parallel Coordinates, Computational Statistics Vol. 13(1), pp.47-63, 1998.
  100. [ISO 9241-11 1998] ISO (International Organization for Standardization): ISO 13407: Human-Centered Design Process for Interactive Systems, 1998.
  101. [ISO, 1988] Information Processing Systems - Open Systems Interconnection - LOTOS - A Formal Description TechniqueBased on temporal Ordering of Observational Behaviour, 1988.
  102. [ISO, 1992] ISO/WD 9241: Part 11 Ergonomic requirements for Office Work with Visual Displays Units, International Standard Organization, 1992.
  103. [ISO, 1999] ISO: Draft International Standard (DIS) 9241:Requirements for Office Work with Visual Display Terminals, Genève, 1999.
  104. [Jambu, 1999] Jambu M. : Méthodes de base de l'analyse des données, Eyrolles 1999.
  105. [Jézéquel et Meyer, 1997] Jézéquel J-M., Meyer B.: Design by contract: The lessons of ariane. Computer (IEEE) , vol. 30(2), pp.129-130, 1997.
  106. [Jinyan et Huiqing, 2002] Jinyan L., Huiqing L.: Kent Ridge Bio-medical Data Set Repository. http://sdmc.lit.org.sg/GEDatasets, 2002, accédé en octobre 2005.
  107. [John et al., 1994] John G.H., Kohavi R., Pfleger K.: Irrelevant Features and the Subset Selection Problem, International Conference on Machine Learning, pp.121-129, 1994.
  108. [John et Langley, 1995] John G.H., Langley P.: Estimating Continuous Distributions in Bayesian Classifiers. Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence, Morgan Kaufmann, San Mateo, pp.338-345, 1995.
  109. [Kalousis et Theoharis, 1999] Kalousis A., Theoharis T.: NOEMON: Design, implementation and performance results of an intelligent assistant for classifier selection. Intelligent Data Analysis, vol. 3 (5), pp.319-337, 1999.
  110. [Kalousis, 2002] Kalousis A.: Algorithm Selection via Meta-Learning. PHD Thesis, Thesis Number:3337. University of Geneve, Department of Computer Science, 2002.
  111. [Kaptelinin, 1995] Kaptelinin V., Kuutti K., Bannon L.: Activity Theory: Basic Concepts and Applications. In Blumenthal et al. (Eds.) Human-Computer Interaction. Lecture Notes in Computer Science. Springer, pp.189-201, 1995.
  112. [Kaptelinin, 1999] Kaptelinin V., Nardi, B.A., Macaulay C.: The Activity Checklist: A Tool For Representing the "Space" of Context, Interactions, pp.27-39, 1999.
  113. [Karat, 1988] Karat, J.: Software evaluation methodologies. In Helander, M. (Ed.). Handbook of human-computer interaction. Amsterdam: Elsevier Science B. V., pp.891-903, 1988.
  114. [Keim et Kriegel, 1994] Keim D.A., Kriegel H.-P.: VisDB: Database Exploration using Multidimensional Visualization, Computer Graphics & Applications Journal, pp.40-49, 1994.
  115. [Keim, 1996] Keim D. A.: Pixel-oriented Visualization Techniques for Exploring Very Large Databases. Journal of Computational and Graphical Statistics, vol. 5(1), pp. 58-77. 1996.
  116. [Kerber et al., 1998] Kerber R., Beck H., Anand T., Smart B.: Actives Templates: Comprehensive Support for Knowledge discovery Process. Intl Conf. on Knowledge Discovery and Data mining, pp.244-248, 1998.
  117. [King et al, 1998] King M.A., Elder IV J.F., Gomolka B., Schmidt E., Summers M., Toop K.: Evaluation of Fourteen Desktop Data Mining Tools. From the 1998 IEEE International Conference on Systems, Man, and Cybernetics, San Diego, CA, pp.12-14, 1998.
  118. [Kira et Rendell, 1992] Kira K., Rendell L.A.: A practical approach to feature selection. In Proc. of the Tenth Int’l Conf. on Machine Learning, pp.500-512, 1992.
  119. [Kodratoff, 1996] Kodratoff Y. : Extraction de connaissances à partir de données : un nouveau sujet pour la recherche scientifique. Actes du XIVème Congré INFORSID, Bordeaux, pp.3-22, 1996.
  120. [Köfp et Iglezakis, 2002] Köfp C., Iglezakis I.: Combination of Task Description Strategies and Case Base Properties for Meta-Learning, Proc of the 2nd Intl. Workshop on Integration and Collaboration Aspects of Data Mining, Decision Support and Meta-Learning (IDDM), pp.65-76, 2002.
  121. [Kohavi, 1995] Kohavi R.: The Power of Decision Tables. In N Lavrac and S Wrobel, editors, Machine Learning: Proceedings of the Eighth European Conference on Machine Learning ECML95, Lecture Notes in Artificial Intelligence 914, Springer Verlag, pp.174-189, 1995.
  122. [Kohavi, 2000] Kohavi R.: Data Mining and Visualization. Invited talk at the National Academy of Engineering US Frontiers of Engineers, Sept 2000. PDF and Compressed postscript. Available in book form ISBN: 0-309-07319-7, 2000.
  123. [Köpf et Iglezakis, 2002] Köfp C., Iglezakis I.: Combination of Task Description Strategies and Case Base Properties for Meta-Learning, Proc of the 2nd Intl. Workshop on Integration and Collaboration Aspects of Data Mining, Decision Support and Meta-Learning (IDDM), pages 65-76, 2002
  124. [Kotsiantis et Pintelas, 2004] Kotsiantis S.B., Pintelas P.E.: Hybrid Feature Selection instead of Ensembles of Classifiers in Medical Decision Support, Proceedings of Information Processing and Management of Uncertainty in Knowledge-Based Systems, July 4-9, Perugia - Italy, pp. 269-276, 2004.
  125. [le Cessie, 1992] le Cessie, S. et van Houwelingen J.C. : Ridge Estimators in Logistic Regression. Applied Statistics, Vol. 41(1), pp.191-201, 1992.
  126. [Leont'ev, 1978] Leont'ev A.N.: Activity, Consciousness, Personality. Englewood Cliffs, NJ, Prentice Hall, 1978.
  127. [Lewis, 1990] Lewis C., Polson P.G., Wharton C., Rieman J.: Testing a walkthrough methodology for theory-based design of walk-up-and-use interfaces. In Chew, J .C., and Schneiderman J. Whiteside eds. CHI'90: Human Factors in Computing Systems. ACM: New York, pp.235-242, 1990.
  128. [Liu et Setiono, 1996] Liu H., Setiono R.: A probabilistic approach to feature selection: a filter solution. In Proc, The 13th International Conference on Machine Learning, pp.319-327, 1996.
  129. [Lohninger, 1994] Lohninger H.: "INSPECT, a program system to visualize and interpret chemical data.", Chemomet. Intell. Lab. Syst. 22 (http://qspr03.tuwien.ac.at/lo/), pp.147-153, 1994.
  130. [Marghescu et al, 2004] Marghescu D., Rajanen M., Back B.: Evaluating the Quality of Use of Visual Data-Mining Tools, in Proc. of 11th European Conference on IT Evaluation, 11-12 November, 2004, Amsterdam, Netherlands, pp. 239-250, 2004.
  131. [Mariage, 2005] Mariage C. : MetroWeb: logiciel de support à l'évaluation de la qualité ergonomique des sites web, Thèse de Doctorat en Sciences de Gestion, UCL, Louvain-la-Neuve, 2005.
  132. [Mayhew, 1992] Mayhew D.J.: Principles and guidelines in software user interface design. Englewood Cliffs, NJ: Prentice Hall, 1992.
  133. [McCall et al, 1977] McCall J.A., Richards P.K., Walters G.F.: Factors in software quality. Vols I-III, Rome Air Development Centre, Italy, 1977.
  134. [Meinadier, 1991] Meinadier J.P. : L'interface utilisateur pour une informatique conviviale, Dunod, 222 p, 1991.
  135. [Metal, 2005] METAL Project, http://www.metal-kdd.org/, accédé en janvier 2005.
  136. [Michie et al, 1994] D. Michie, D.J. Spiegelhalter, C.C. Taylor, (eds.), Machine Learning, Neural and Statistical Classification Ellis Horwood, 1994.
  137. [Monk et al, 1993] Monk A., Wright P., Haber J., Davenport L.: Improving your human-computer interface: A practical technique. Hemel Hempstead, UK: Prentice Hall, 1993.
  138. [Morses et al., 2000] Morse E., Lewis M., Olsen K.A.: Evaluating visualization: using a taxonomic guide”, International Journal of Human-Computer Studies, Vol. 53, pp.637-662, 2000.
  139. [Murine et Carpenter, 1984] Murine G., Carpenter C.: Measuring software product quality. Quality progress, Vol 7(5), pp.16-20, 1984.
  140. [Nielsen et Mollich, 1990] Nielson J., Mollich R.: Heuristic evaluation of user interfaces, CHI'90 ACM, New York, pp.249-256, 1990.
  141. [Nielsen et Philipps, 1993b] Nielsen J., Philipps V.L., Estimating the Relative Usability of Two Interfaces: Heuristic, Formal, and Empirical Methods Compared in Proceedings of InterCHI'93, pp.214-221, 1993.
  142. [Nielsen, 1993a] Nielsen J., Usability Engineering, Academic Press Inc., ISBN 0-12-518405-0, 1983.
  143. [Nielsen, 1994] Nielsen J. 1994. Estimating the number of subjects needed for a thinking aloud test. International Journal of Human-Computer Studies, 41 (3), pp.385-397, 1994.
  144. [Norman, 1986] Norman D.A., Draper S.W., User Centered System Design: New Perspectives on Human Factors Interaction, Lawrence Erlbaum Associates, Publishers, Hillsdale, New Jersey, 1986.
  145. [Oudshoorn et al., 1996] Oudshoorn M.J., Widjaja H., Ellershaw S.K. : Aspects and Taxonomy of Program Visualization, World Scientific, Singapore, pp.3-26, 1996.
  146. [Petrak, 2000] Petrak J., Fast Subsampling Performance Estimates for Classification Algorithm Selection In Keller J. and Giraud-Carrier C. Eds. ECML-2000 Workshop Notes on Meta Learning: Building Automatic Advice Strategies for Model Selection and Method Combination, Barcelona, Spain, pp.3–14, 2000.
  147. [Picket et Grinstein, 1988] Pickett R.M., Grinstein G.: Iconographic displays for visualizing multidimensional data. In Proc. of the 1988 IEEE International Conference on Systems, Man, and Cybernetics , volume 1, pp.514-519, 1988.
  148. [Pickett, 1970] Pickett R.M.: Visual analyses of texture in the detection and recognition of objects, in B. S. Lipkin and A. Rosenfeld, editors, Picture Processing and Psycho-Pictorics. Academic Press, New York, pp. 298-308, 1970.
  149. [Platt, 1998] Platt J.: Fast Training of Support Vector Machines using Sequential Minimal Optimization. Advances in Kernel Methods - Support Vector Learning, B. Schölkopf, C. Burges, and A. Smola, eds., MIT Press, 1998.
  150. [Pollier, 1991] Pollier A., Evaluation d’une interface par des ergonomes : Diagnostics et Stratégies, Rapport Technique INRIA n°1391, Février 1991.
  151. [Poulet, 2001] Poulet F. : CubeVis : Voir pour mieux comprendre, XXXIIIe Journées de Statistiques, Nantes, 2001.
  152. [Poulet, 2002a] Poulet F., Full-View: A Visual Data-Mining Environment, in International Journal of Image and Graphics, Vol.2, N.1, pp.127-144, 2002.
  153. [Poulet, 2002b] Poulet F.: Cooperation between automatic algorithms, interactive algorithms and visualization tools for visual data mining. In Proc. of Visual Data Mining workshop, PKDD2002, pp. 67-79, 2002.
  154. [Poulet, 2004] Poulet F.: SVM and Graphical Algorithms: A Cooperative Approach, in proc. of ICDM 2004, pp. 499-502, 2004.
  155. [Preece, 1993] Preece J.: (ed) Guide to Usability: Human Factors in Computing, Addsion-Wesley, Wokingham, England, 1993.
  156. [Quinlan, 1993] Quinlan R.: C4.5: Programs for Machine Learning, Morgan Kaufmann Publishers, San Mateo, CA, 1993.
  157. [Rao et Card, 1994] Rao R., Card S.K.: The Table Lens: Merging Graphical and Symbolic Representations in an Interactive Focus +Context Visualization for Tabular Information, in Proc. of CHI'94, Boston, ACM Press, pp.318-322, 1994.
  158. [Robertson et al, 1991] Robertson G.G., Mackinlay J.D., Card S.K.: Cone Trees: animated 3D visualizations of hierarchical information, in Proc. of the SIGCHI conference on Human factors in computing systems: Reaching through technology, pp.189-194, 1991.
  159. [Saporta, 2005] Saporta G. : Data mining: une nouvelle façon de faire de la statisque. http://cedric.cnam.fr/~saporta/DM.pdf, 2005, accédé en mars 2005.
  160. [Scapin et Bastien, 1997] Scapin D., Bastien C.H., Ergonomic criteria for evaluating the ergonomic quality of interactive systems, Behaviour & Information Technologie 16, pp.220-231, 1997.
  161. [Schneiderman, 1992] Schneiderman B.: Designing the User Interface: Strategies for Effective Human-Computer Interaction. Reading, MA : Addison-Wesley, 1992.
  162. [Schneiderman, 1996] Shneiderman B.: The Eyes Have It: A Task by Data Type Taxonomy For Information Visualizations, in Proc. of IEEE Symposium on Visual Languages, IEEE Service Center, Sep 3-6, pp.336-343, 1996.
  163. [Seewald, 2002] Seewald A.K.: Meta-Learning for Stacked Classification (extended version). In Proceedings of the Second International Workshop on Integration and Collaboration Aspects of Data Mining, Decision Support and Meta-Learning (IDDM-2002), University of Helsinki, Department of Computer Science, Report B-2002-3, 2002.
  164. [Senach, 1990] Senach B., Evaluation ergonomique des Interfaces Homme-Machine : une revue de la littérature, Rapport de l'INRIA n°1180, Mars 1990.
  165. [Seuren, 1996] Seuren M.: Design and Implementation of an Automatic Event Abstraction Tool. PhD thesis, Waterloo, Ontario, Canada, 1996.
  166. [Smith et Mosier, 1986] Smith S.L., Mosier J.N.: Guidelines for designing user interface software. Massachusetts, USA: The MITRE corporation, 1986.
  167. [Stasko et al., 2000] Stasko J., Catrambone R., Guzdial M., McDonald K.: An evaluation of spacefilling information visualizations for depicting hierarchical structures”, International Journal of Human-Computer Studies, Vol. 53, pp.663-694, 2000.
  168. [Suchman, 1987] Suchman, L. A. (1987). Plans and situated actions: The problem of human-machine communications. Cambridge, UK: Cambridge University Press.
  169. [Sun, 1999] Sun: Java Look and Feel Design Guidelines, Microsystems, Inc., Palo Alto, accessible à http://java.sun.com/products/jlf/edl/dg/index.htm, 1999, accédé en janvier 2005.
  170. [Tegarden, 1999] Tegarden D. P.: Business information visualization. Communications of the AIS. Vol. 1, Article 4 (January), 1999.
  171. [Tricot et al., 2003] Tricot A., Plégat-Soutjis F., Camps J.-F., Amiel A., Lutz G., Morcillo A. (2003). Utilité, utilisabilité, acceptabilité : interpréter les relations entre trois dimensions de l'évaluation des EIAH. Dans Desmoulins, C., Marquet, P., Bouhineau, D. (Dir.), "Environnements Informatiques pour l'Apprentissage Humain 2003". Strasbourg : ATIEF ; INRP. 391-402. [OAI : oai:archive-edutice.ccsd.cnrs.fr:edutice-00000154_v1] - http://archive-edutice.ccsd.cnrs.fr/edutice-00000154.
  172. [Tufte, 1990] Tufte E.R.: Envisioning Information. Graphic Press, 1990.
  173. [Tufte, 1993] Tufte E.R.: The Visual Display Of Quantitative Information. Graphic Press, 1993.
  174. [Vanderdonckt, 1994] Vanderdonckt J. : Guide ergonomique de la présentation des applications hautement interactives, Presses Universitaires, Namur, 1994.
  175. [Vanderdonckt, 1998] Vanderdonckt J. : Conception ergonomique de pages WEB, Vesale, 1998.
  176. [Vansnick, 1990] Vansnick J.C.: Measurement theory and decision aid, in Bana e Costa (ed.), Readings in Multiple Criteria Decision Aid, Springer-Verlog, Berlin, pp.81-100, 1990.
  177. [Ware et al., 2001] Malcolm Ware M., Eibe F., Holmes G., Hall M., Witten I.H.: Interactive Machine Learning: Letting Users Build Classifiers. International Journal of Human-Computer Studies, Vol.55, No.3, pp.281-292, 2001.
  178. [Wharton et al., 1994] Wharton, C., Rieman, J., Lewis, C., & Polson, P. (1994). The cognitive walkthrough method: A practitioner's guide. In Nielsen, J., & Mack, R. L. (Eds.), Usability inspection methods, New York, NY: John Wiley & Sons, pp.105-140, 1994.
  179. [Whiteside et al., 1988] Whiteside J., Bennett J., Holtzblatt K.: Usability engineering: our experience and evolution. In M. Helander, Ed. Handbook of Human Computer Interaction, Amsterdam: Elsevier, pp.791-817, 1988.
  180. [Winkler, 1968] Winkler R. L.: The consensus of subjective probability distributions. Management Science, vol.15(2), pp.61–75, 1968.
  181. [Witten et Eibe, 2005] Witten I.H., Eibe F.: Data Mining: Practical machine learning tools and techniques, 2nd Edition, Morgan Kaufmann, San Francisco, 2005.
  182. [Wolf, 1989] Wolf C.G.: The role of laboratory experiments in HCI: help, hindrance or Ho-hum? (Panel session). Proceedings of CHI+89 conference, Austin, TX, 30 April-4 May 1989. New York: ACM, pp. 265-268, 1989.
  183. [Wolpert et Macready, 1997] D. H. Wolpert, W. G. Macready, No Free Lunch Theorems for Optimization, IEEE Transactions on Evolutionary Computation, vol.1, pp.67–82, 1997.
  184. [Zighed et Rakotomalala, 2003] Zighed A.D., Rakotomalala R. : Extraction de connaissances à partir des données (ECD). Techniques de l’Ingénieur, H3 744, pp.1-26, 2003.