Overview

The ideas and techniques worked out in Rough Set Theory allow for knowledge reduction and to finding near - to - functional dependencies in data. This fact determines the importance of these techniques for the rapidly growing field of knowledge discovery. Volume 1 and 2 will bring together articles covering the present state of the methods developed in this field of research. Among the topics covered we may mention: rough mereology and rough mereological approach to knowledge discovery in distributed systems; discretization and quantization of attributes; morphological aspects of rough set theory; analysis of default rules in the framework of rough set theory.

Full Product Details

Author:   Lech Polkowski ,  Andrzej Skowron
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Physica-Verlag GmbH & Co
Edition:   1998 ed.
Volume:   19
Dimensions:   Width: 15.50cm , Height: 3.30cm , Length: 23.50cm
Weight:   3.040kg
ISBN:  

9783790811209

ISBN 10:   3790811203
Pages:   601
Publication Date:   20 August 1998
Audience:   College/higher education ,  Professional and scholarly ,  Postgraduate, Research & Scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

1. Introducing the Book.- 1. Applications.- 2. Rough Approximation of a Preference Relation in a Pairwise Comparison Table.- 3. Learning Decision Rules from Similarity Based Rough Approximations.- 4. Discovery of Data Patterns with Applications to Decomposition and Classification Problems.- 5. Answering Non-Standard Queries in Distributed Knowledge-Based Systems.- 6. Approximation Spaces, Reducts and Representatives.- 7. Data Mining: A Probabilistic Rough Set Approach.- 2: Case Studies.- 8. Soft Processing of Audio Signals.- 9. A Rough Set Approach to Information Retrieval.- 10. Extraction Method Based on Rough Set Theory of Rule-Type Knowledge from Diagnostic Cases of Slope-Failure Danger Levels.- 11. Soft Computing-Based Recognition of Musical Sounds.- 12. Rough Sets in Industrial Applications.- 13. Rough Sets in Economic Applications.- 14. Multistage Rough Set Analysis of Therapeutic Experience with Acute Pancreatitis.- 15. Reduction Methods for Medical Data.- 16. Formalization and Induction of Medical Expert System Rules Based on Rough Set Theory.- 17. Rough Sets for Database Marketing.- 18. A New Halftoning Method Based on Error Diffusion with Rough Set Filtering.- 3: Hybrid Approaches.- 19. IRIS Revisited: A Comparison of Discriminant and Enhanced Rough Set Data Analysis.- 20. Applications of Rough Patterns.- 21. Time and Clock Information Systems: Concepts and Roughly Fuzzy Petri Net Models.- 22. The Synthesis Problem of Concurrent Systems Specified by Dynamic Information Systems.- 23. Rough Sets and Artificial Neural Networks.- 24. Genetic Algorithms in Decomposition and Classification Problems.- Appendix 1: Rough Set Bibliography.- Selected Bibliography on Rough Sets.- Appendix 2: Software Systems.- GROBIAN.- RSDM: Rough sets Data Miner, A System to Add Data Mining Capabilities to RDBMS.- LERS — A Knowledge Discovery System.- TRANCE: A Tool for Rough Data Analysis, Classification, and Clustering.- ProbRough — A System for Probabilistic Rough Classifiers Generation.- The ROSETTA Software System.- RSL — The Rough Set Library.- Rough Family — Software Implementation of the Rough Set Theory.- TAS: Tools for Analysis and Synthesis of Concurrent Processes Using Rough Set Methods.- RoughFuzzyLab — A System for Data Mining and Rough and Fuzzy Sets Based Classification.- PRIMEROSE.- KDD-R: Rough Sets-Based Data Mining System.

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