Statistical Implicative Analysis: Theory and Applications

✍ Scribed by Régis Gras, Régis Gras, Einoshin Suzuki, Fabrice Guillet, Filippo Spagnolo

• Publisher: Springer
• Year: 2008
• Tongue: English
• Leaves: 496
• Series: Studies in Computational Intelligence
• Edition: 1
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

front-matter......Page 1
00......Page 22
01......Page 52
02......Page 65
03......Page 82
04......Page 106
05......Page 125
06......Page 137
07......Page 169
08......Page 191
09......Page 209
10......Page 230
11......Page 249
12......Page 279
13......Page 301
14......Page 322
15......Page 347
16......Page 380
17......Page 393
18......Page 406
19......Page 433
20......Page 447
21......Page 464
back-matter......Page 490