Editors:
- Presents latest results in statistical implicative analysis
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI)
Buy it now
Buying options
Tax calculation will be finalised at checkout
Other ways to access
This is a preview of subscription content, log in via an institution to check for access.
Table of contents (22 chapters)
-
Extensions to rule interestingness in data mining
-
Back Matter
About this book
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.
Editors and Affiliations
-
LINA, FRE 2729 CNRS, France
Régis Gras
-
Department of Informatics, Kyushu University, Nishi, Japan
Einoshin Suzuki
-
LINA, FRE 2729 CNRS, Polytech'Nantes, Nantes, France
Fabrice Guillet
-
Dipartimento di Matematica, Univesritàa di Palermo, Italy
Filippo Spagnolo
Bibliographic Information
Book Title: Statistical Implicative Analysis
Book Subtitle: Theory and Applications
Editors: Régis Gras, Einoshin Suzuki, Fabrice Guillet, Filippo Spagnolo
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-540-78983-3
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2008
Hardcover ISBN: 978-3-540-78982-6Published: 29 April 2008
Softcover ISBN: 978-3-642-09777-5Published: 25 November 2010
eBook ISBN: 978-3-540-78983-3Published: 06 July 2008
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XV, 513
Topics: Mathematical and Computational Engineering, Artificial Intelligence, Applications of Mathematics