{"product_id":"9783540789826","title":"Statistical Implicative Analysis : Theory and Applications (Studies in Computational Intelligence) \u003cVol. 127\u003e","description":"Statistical implicative analysis is a data analysis method with a significant impact on a variety of areas ranging from pedagogical research to data mining. This volume collects significant research contributions from disciplines that benefit from SIA. \u003cp\u003eStatistical implicative analysis is a data analysis method created by Régis Gras almost thirty years ago which has a significant impact on a variety of areas ranging from pedagogical and psychological research to data mining. Statistical implicative analysis (SIA) provides a framework for evaluating the strength of implications; such implications are formed through common knowledge acquisition techniques in any learning process, human or artificial. This new concept has developed into a unifying methodology, and has generated a powerful convergence of thought between mathematicians, statisticians, psychologists, specialists in pedagogy and last, but not least, computer scientists specialized in data mining.\u003c\/p\u003e\u003cp\u003eThis volume collects significant research contributions of several rather distinct disciplines that benefit from SIA. Contributions range from psychological and pedagogical research, bioinformatics, knowledge management, and data mining.\u003c\/p\u003e Methodology and concepts for SIA.- An overview of the Statistical Implicative Analysis (SIA) development.- CHIC: Cohesive Hierarchical Implicative Classification.- Assessing the interestingness of temporal rules with Sequential Implication Intensity.- Application to concept learning in education, teaching, and didactics.- Student's Algebraic Knowledge Modelling: Algebraic Context as Cause of Student's Actions.- The graphic illusion of high school students.- Implicative networks of student's representations of Physical Activities.- A comparison between the hierarchical clustering of variables, implicative statistical analysis and confirmatory factor analysis.- Implications between learning outcomes in elementary bayesian inference.- Personal Geometrical Working Space: a Didactic and Statistical Approach.- A methodological answer in various application frameworks.- Statistical Implicative Analysis of DNA microarrays.- On the use of Implication Intensity for matching ontologies and textual taxonomies.- Modelling by Statistic in Research of Mathematics Education.- Didactics of Mathematics and Implicative Statistical Analysis.- Using the Statistical Implicative Analysis for Elaborating Behavioral Referentials.- Fictitious Pupils and Implicative Analysis: a Case Study.- Identifying didactic and sociocultural obstacles to conceptualization through Statistical Implicative Analysis.- Extensions to rule interestingness in data mining.- Pitfalls for Categorizations of Objective Interestingness Measures for Rule Discovery.- Inducing and Evaluating Classification Trees with Statistical Implicative Criteria.- On the behavior of the generalizations of the intensity of implication: A data-driven comparative study.- The TVpercent principle for the counterexamples statistic.- User-SystemInteraction for Redundancy-Free Knowledge Discovery in Data.- Fuzzy Knowledge Discovery Based on Statistical Implication Indexes.","brand":"Springer","offers":[{"title":"Default Title","offer_id":52359283409207,"sku":"00000_00000_00000_00000","price":1191.9,"currency_code":"MYR","in_stock":true}],"url":"https:\/\/kinokuniya.com.my\/products\/9783540789826","provider":"Books Kinokuniya Malaysia","version":"1.0","type":"link"}