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Statistical Implicative Analysis
Statistical 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. This 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.
The Theory of Statistical Implicative Analysis
This book summarizes the methods and concepts of Statistical Implicative Analysis (SIA), created by Rgis Gras in the 1980s to study, in a new way, the behavioural responses of French pupils to mathematics tests. Using a multidimensional, non-symmetrical data analysis method, SIA crosses a set of subjects or objects with a set of variables. It effectively complements traditional correlational and psychometric methods. SIA, through its various extensions, is today presented as a broad Artificial Intelligence method aimed at extracting trends and possible causalities in the form of rules, from a set of variables. It is based on the unlikeliness of the existence of these relationships, i.e. on t...
The Theory of Statistical Implicative Analysis
This book summarizes the methods and concepts of Statistical Implicative Analysis (SIA), created by Régis Gras in the 1980s to study, in a new way, the behavioural responses of French pupils to mathematics tests. Using a multidimensional, non-symmetrical data analysis method, SIA crosses a set of subjects or objects with a set of variables. It effectively complements traditional correlational and psychometric methods. SIA, through its various extensions, is today presented as a broad Artificial Intelligence method aimed at extracting trends and possible causalities in the form of rules, from a set of variables. It is based on the unlikeliness of the existence of these relationships, i.e. on...
Statistical Data Mining and Knowledge Discovery
Massive data sets pose a great challenge to many cross-disciplinary fields, including statistics. The high dimensionality and different data types and structures have now outstripped the capabilities of traditional statistical, graphical, and data visualization tools. Extracting useful information from such large data sets calls for novel approaches that meld concepts, tools, and techniques from diverse areas, such as computer science, statistics, artificial intelligence, and financial engineering. Statistical Data Mining and Knowledge Discovery brings together a stellar panel of experts to discuss and disseminate recent developments in data analysis techniques for data mining and knowledge extraction. This carefully edited collection provides a practical, multidisciplinary perspective on using statistical techniques in areas such as market segmentation, customer profiling, image and speech analysis, and fraud detection. The chapter authors, who include such luminaries as Arnold Zellner, S. James Press, Stephen Fienberg, and Edward K. Wegman, present novel approaches and innovative models and relate their experiences in using data mining techniques in a wide range of applications.
Theory of Didactical Situations in Mathematics
This book is unique. It gathers texts which give the best presentation of the principles and key concepts of the Theory of Didactical Situations that Guy Brousseau developed in the period from 1970 to 1990. These texts provide a comprehensive presentation of the Theory. In order to facilitate the reading of certain points footnotes have been added, as well as preludes and interludes to place in context the chosen texts and clarify the construction of the book.
The Gourmet Cookbook
Gathers recipes published in Gourmet magazine over the last six decades, including beef Wellington, seared salmon with balsamic glaze, and other entrées, hors d'oeuvres, side dishes, ethnic specialties, and desserts.
Source Book of Flavors
Abstract: Basic information is provided for food technologists, flavor chemists, and other food-related professionals, covering major flavor-allied topics; these include: the flavor industry; the flavor chemist; flavor research; flavor chemistry; food colorants; flavor manufacturing methods; application of flavor quality assurance; flavor legislation in the US and abroad; worldwide labeling regulations; and toxicology and consumer safety. Available data are provided on: natural flavoring materials (e.g., alliaceous and fruit flavors, herbs, spices, essential oils); 325 plant materials, principal essential oils, and organic chemicals used in flavorings; synthetic flavors; aromatics; GRAS flavorings; and 350 flavor formulations. A bibliography on flavoring materials which occur naturally or as a result of processing is included. The legalized exemption of certain food additives (including flavoring additives) from US tolerance requirements is highlighted separately. Over 3000 literaturereferences are provided throughout the material. (wz).
