Rough Set Methods and Applications: New Developments in Knowledge Discovery in Information Systems

by Polkowski, Lech; Tsumoto, Shusaku; Lin, Tsau Y.

• ISBN13: 9783790813289
• ISBN10: 3790813281
• Format: Hardcover
• Copyright: 2001-01-01
• Publisher: Springer-Verlag New York Inc

Summary

Rough set approach to reasoning under uncertainty is based on inducing knowledge representation from data under constraints expressed by discernibility or, more generally, similarity of objects. Knowledge derived by this approach consists of reducts, decision or association rules, dependencies, templates, or classifiers. This monograph presents the state of the art of this area. The reader will find here a deep theoretical discussion of relevant notions and ideas as well as rich inventory of algorithmic and heuristic tools for knowledge discovery by rough set methods. An extensive bibliography will help the reader to get an acquaintance with this rapidly growing area of research.

Table of Contents

Foreword	vii
Z. Pawlak
PART 1. INTRODUCTION
Introducing the Book	3	(6)
L. Polkowski
S. Tsumoto
T.Y. Lin
A Rough Set Perspective on Knowledge Discovery in Information Systems: An Essay on the Topic of the Book	9	(40)
L. Polkowski
S. Tsumoto
T.Y. Lin
PART 2. METHODS AND APPLICATIONS: REDUCTS, SIMILARITY, MEREOLOGY
Rough Set Algorithms in Classification Problem	49	(40)
J.G. Bazan
Hung Son Nguyen
Sinh Hoa Nguyen
P. Synak
J. Wroblewski
Rough Mereology in Information Systems. A Case Study: Qualitative Spatial Reasoning	89	(48)
L. Polkowski
A. Skowron
Knowledge Discovery by Application of Rough Set Models	137	(98)
J. Stepaniuk
Various Approaches to Reasoning with Frequency Based Decision Reducts: A Survey	235	(54)
D. Slezak
PART 3. METHODS AND APPLICATIONS: REGULAR PATTERN EXTRACTION, CONCURRENCY
Regularity Analysis and its Applications in Data Mining	289	(90)
Sinh Hoa Nguyen
Rough Set Methods for the Synthesis and Analysis of Concurrent Processes	379	(112)
Z. Suraj
PART 4. METHODS AND APPLICATIONS: ALGEBRAIC AND STATISTICAL ASPECTS, CONFLICTS, INCOMPLETENESS
Conflict Analysis	491	(30)
R. Deja
Logical and Algebraic Techniques for Rough Set Data Analysis	521	(24)
I. Duntsch
G. Gediga
Statistical Techniques for Rough Set Data Analysis	545	(22)
G. Gediga
I. Duntsch
Data Mining in Incomplete Information Systems from Rough Set Perspective	567	(16)
M. Kryszkiewicz
H. Rybinski
PART 5. AFTERWORD
Rough Sets and Rough Logic: A KDD Perspective	583	(66)
Z. Pawlak
L. Polkowski
A. Skowron
Appendix: Selected Bibliofgraphy on Rough Sets
Bibliography	649