Statistical Implicative Analysis 2008

Methodology and concepts for SIA

• Régis Gras, Pascale Kuntz:
  An overview of the Statistical Implicative Analysis (SIA) development. 11-40
  
• Raphaël Couturier:
  CHIC: Cohesive Hierarchical Implicative Classification. 41-53
  
• Julien Blanchard, Fabrice Guillet, Régis Gras:
  Assessing the interestingness of temporal rules with Sequential Implication Intensity. 55-71
  

Application to concept learning in education, teaching, and didactics

• Marie-Caroline Croset, Jana Trgalova, Jean-François Nicaud Croset:
  Student's Algebraic Knowledge Modelling: Algebraic Context as Cause of Student's Actions. 75-98
  
• Catherine-Marie Chiocca, Ingrid Verscheure:
  Implicative networks of student's representationsof Physical Activities. 119-130
  
• Iliada Elia, Athanasios Gagatsis:
  A comparison between the hierarchical clustering of variables, implicative statistical analysis and confirmatory factor analysis. 131-162
  
• Carmen Díaz, Inmaculada de la Fuente, Carmen Batanero:
  Implications between learning outcomes in elementary bayesian inference. 163-184
  
• Alain Kuzniak:
  Personal Geometrical Working Space: a Didactic and Statistical Approach. 185-202
  

A methodological answer in various application frameworks

• Gérard Ramstein:
  Statistical Implicative Analysis of DNA microarrays. 205-225
  
• Jérôme David, Fabrice Guillet, Henri Briand, Régis Gras:
  On the use of Implication Intensity for matching ontologies and textual taxonomies. 227-245
  
• Elsa Malisani, Aldo Scimone, Filippo Spagnolo:
  Modelling by Statistic in Research of Mathematics Education. 247-276
  
• Dominique Lahanier-Reuter:
  Didactics of Mathematics and Implicative Statistical Analysis. 277-298
  
• Stéphane Daviet, Fabrice Guillet, Henri Briand, Serge Baquédano, Vincent Philippé, Régis Gras:
  Using the Statistical Implicative Analysis for Elaborating Behavioral Referentials. 299-319
  
• Pilar Orús, Pablo Gregori:
  Fictitious Pupils and Implicative Analysis: a Case Study. 321-345
  
• Nadja Maria Acioly-Régnier, Jean-Claude Régnier:
  Identifying didactic and sociocultural obstacles to conceptualization through Statistical Implicative Analysis. 347-379
  

Extensions to rule interestingness in data mining

• Einoshin Suzuki:
  Pitfalls for Categorizations of Objective Interestingness Measures for Rule Discovery. 383-395
  
• Gilbert Ritschard, Vincent Pisetta, Djamel A. Zighed:
  Inducing and Evaluating Classification Trees with Statistical Implicative Criteria. 397-419
  
• Benoît Vaillant, Stéphane Lallich, Philippe Lenca:
  On the behavior of the generalizations of the intensity of implication: A data-driven comparative study. 421-447
  
• Ricco Rakotomalala, Alain Morineau:
  The TVpercentprinciple for the counterexamples statistic. 449-462
  
• Rémi Lehn, Henri Briand, Fabrice Guillet:
  User-System Interaction for Redundancy-Free Knowledge Discovery in Data. 463-479
  
• Maurice Bernadet:
  Fuzzy Knowledge Discovery Based on Statistical Implication Indexes. 481-506