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Rough Sets in Knowledge Discovery 2: Applications, Case Studies & Software Systems

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Rough Sets in Knowledge Discovery 2: Applications, Case Studies & Software Systems Cover

 

Synopses & Reviews

Publisher Comments:

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.

Synopsis:

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.

Table of Contents

1. Methodology and applications — 2. Applications, case studies and software systems.

Product Details

ISBN:
9783790811209
Editor:
Polkowski, L.
Editor:
Kacprzyk, J.
Editor:
Kacprzyk, J.
Editor:
Skowron, A.
Editor:
Polkowski, L.
Author:
Polkowski, L.
Author:
Polkowski, Lech
Editor:
Skowron, A.
Publisher:
Physica-Verlag
Location:
Heidelberg ;
Subject:
Logic
Subject:
Expert Systems
Subject:
Expert systems (computer science)
Subject:
Management Information Systems
Subject:
Artificial Intelligence
Subject:
Database management
Subject:
Set Theory
Subject:
Soft computing
Subject:
Artificial Intelligence - General
Subject:
Intelligence (AI) & Semantics
Subject:
Mathematics-Logic and Philosophy
Subject:
Information Management
Subject:
Data analysis
Subject:
Data mining
Subject:
Datenanalyse
Subject:
Decision Support Techniques.
Subject:
Fuzzy logic
Subject:
Rough sets.
Subject:
Techniken der Entscheidungsfindung
Subject:
BUSINESS INFORMATION SYSTEMS
Subject:
Artificial Intelligence (incl. Robotics)
Subject:
Economics
Subject:
Language, literature and biography
Subject:
Engineering
Copyright:
Edition Description:
Book
Series:
Studies in Fuzziness and Soft Computing
Series Volume:
18-<19 >
Publication Date:
19981001
Binding:
HARDCOVER
Language:
English
Illustrations:
Yes
Pages:
611
Dimensions:
235 x 155 mm 3040 gr

Related Subjects

Arts and Entertainment » Art » History and Criticism
Business » High Tech Management
Computers and Internet » Artificial Intelligence » General
Computers and Internet » Computers Reference » General
Computers and Internet » Database » Applications
Science and Mathematics » Mathematics » Foundations and Logic
Science and Mathematics » Mathematics » Geometry » Geometry and Trigonometry
Science and Mathematics » Mathematics » Logic and Philosophy
Science and Mathematics » Mathematics » Set Theory

Rough Sets in Knowledge Discovery 2: Applications, Case Studies & Software Systems New Hardcover
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Product details 611 pages Springer-Verlag New York, Incorporated - English 9783790811209 Reviews:
"Synopsis" by , 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.
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