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Transactions on Rough Sets IX

  • Book
  • © 2008

Overview

Editors:
  1. James F. Peters

    1. Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, Canada

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  2. Andrzej Skowron

    1. Institute of Mathematics, Warsaw University, Warsaw, Poland

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    You can also search for this editor in PubMed   Google Scholar

  3. Henryk Rybiński

    1. Institute of Computer Science, Warsaw University of Technology, Warsaw, Poland

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 5390)

Part of the book sub series: Transactions on Rough Sets (TRS)

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Table of contents (26 chapters)

  1. Front Matter

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  2. Vagueness and Roughness

    • Zbigniew Bonikowski, Urszula Wybraniec-Skardowska
    Pages 1-13

  3. Modified Indiscernibility Relation in the Theory of Rough Sets with Real-Valued Attributes: Application to Recognition of Fraunhofer Diffraction Patterns

    • Krzysztof A. Cyran
    Pages 14-34

  4. On Certain Rough Inclusion Functions

    • Anna Gomolińska
    Pages 35-55

  5. Automatic Rhythm Retrieval from Musical Files

    • Bożena Kostek, Jarosław Wójcik, Piotr Szczuko
    Pages 56-75

  6. FUN: Fast Discovery of Minimal Sets of Attributes Functionally Determining a Decision Attribute

    • Marzena Kryszkiewicz, Piotr Lasek
    Pages 76-95

  7. Information Granulation: A Medical Case Study

    • Urszula Kużelewska, Jarosław Stepaniuk
    Pages 96-113

  8. Maximum Class Separability for Rough-Fuzzy C-Means Based Brain MR Image Segmentation

    • Pradipta Maji, Sankar K. Pal
    Pages 114-134

  9. Approximation Schemes in Logic and Artificial Intelligence

    • Victor W. Marek, Mirosław Truszczyński
    Pages 135-144

  10. Decision Rule Based Data Models Using NetTRS System Overview

    • Marcin Michalak, Marek Sikora
    Pages 145-156

  11. A Rough Set Based Approach for ECG Classification

    • Sucharita Mitra, M. Mitra, B. B. Chaudhuri
    Pages 157-186

  12. Universal Problem of Attribute Reduction

    • Mikhail Ju. Moshkov, Marcin Piliszczuk, Beata Zielosko
    Pages 187-199

  13. Extracting Relevant Information about Reduct Sets from Data Tables

    • Mikhail Ju. Moshkov, Andrzej Skowron, Zbigniew Suraj
    Pages 200-211

  14. Context Algebras, Context Frames, and Their Discrete Duality

    • Ewa Orłowska, Ingrid Rewitzky
    Pages 212-229

  15. A Study in Granular Computing: On Classifiers Induced from Granular Reflections of Data

    • Lech Polkowski, Piotr Artiemjew
    Pages 230-263

  16. On Classifying Mappings Induced by Granular Structures

    • Lech Polkowski, Piotr Artiemjew
    Pages 264-286

  17. The Neurophysiological Bases of Cognitive Computation Using Rough Set Theory

    • Andrzej W. Przybyszewski
    Pages 287-317

  18. Diagnostic Feature Analysis of a Dobutamine Stress Echocardiography Dataset Using Rough Sets

    • Kenneth Revett
    Pages 318-327

  19. Rules and Apriori Algorithm in Non-deterministic Information Systems

    • Hiroshi Sakai, Ryuji Ishibashi, Kazuhiro Koba, Michinori Nakata
    Pages 328-350

  20. On Extension of Dependency and Consistency Degrees of Two Knowledges Represented by Covering

    • P. Samanta, Mihir K. Chakraborty
    Pages 351-364
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Keywords

About this book

The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence.

This book, which constitutes the ninth volume of the Transactions on Rough Sets series, providing evidence of the continuing growth of a number of research streams. It includes articles that are extensions of papers included in the first conference on Rough Sets and Intelligent Systems Paradigms.

The 26 papers presented in this volume introduce a number of new advances in the foundations and applications of artificial intelligence, engineering, image processing, logic, mathematics, medicine, music, and science.  

Reviews

From the reviews: “Pawlak originally developed rough sets to be used in the same situations as Zadeh’s better-known fuzzy sets … . Although they are less popular than fuzzy sets, they do have a devoted following and are proven to be a good tool when properly applied. … the quality and significance of the contributions vary considerably. … the book emphasizes that rough set theory is a viable tool in artificial intelligence and other areas of data handling … which makes it worth keeping in one’s mental toolbox.” (Jonathan Golan, ACM Computing Reviews, December, 2009)

Editors and Affiliations

  • Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, Canada

    James F. Peters

  • Institute of Mathematics, Warsaw University, Warsaw, Poland

    Andrzej Skowron

  • Institute of Computer Science, Warsaw University of Technology, Warsaw, Poland

    Henryk Rybiński

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