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Rough Sets in Knowledge Discovery 2

Applications, Case Studies and Software Systems

  • Book
  • © 1998

Overview

Editors:
  1. Lech Polkowski

    1. Institute of Mathematics, Warsaw University of Technology, Warsaw, Poland
      Polish-Japanese Institute of Computer Techniques, Warsaw, Poland

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    You can also search for this editor in PubMed   Google Scholar

  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

  • Provides many very interesting results
  • Marks out future directions of developments of this domain

Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 19)

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Table of contents (24 chapters)

  1. Front Matter

    Pages I-X
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  2. Introducing the Book

    1. Introducing the Book

      • Lech Polkowski, Andrzej Skowron
      Pages 1-9

  3. Applications

    1. Front Matter

      Pages 11-11
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    2. Rough Approximation of a Preference Relation in a Pairwise Comparison Table

      • Salvatore Greco, Benedetto Matarazzo, Roman SÅ‚owiÅ„ski
      Pages 13-36

    3. Learning Decision Rules from Similarity Based Rough Approximations

      • Krzysztof Krawiec, Roman SÅ‚owiÅ„ski, Daniel Vanderpooten
      Pages 37-54

    4. Discovery of Data Patterns with Applications to Decomposition and Classification Problems

      • Sinh Hoa Nguyen, Andrzej Skowron, Piotr Synak
      Pages 55-97

    5. Answering Non-Standard Queries in Distributed Knowledge-Based Systems

      • Zbigniew W. Ras
      Pages 98-108

    6. Approximation Spaces, Reducts and Representatives

      • Jaroslaw Stepaniuk
      Pages 109-126

    7. Data Mining: A Probabilistic Rough Set Approach

      • Ning Zhong, Ju-Zhen Dong, Setsuo Ohsuga
      Pages 127-144

  4. Case Studies

    1. Front Matter

      Pages 145-145
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    2. Soft Processing of Audio Signals

      • Andrzej Czyżewski
      Pages 147-165

    3. A Rough Set Approach to Information Retrieval

      • Kaname Funakoshi, Tu Bao Ho
      Pages 166-177

    4. Extraction Method Based on Rough Set Theory of Rule-Type Knowledge from Diagnostic Cases of Slope-Failure Danger Levels

      • Hitoshi Furuta, Michiyuki Hirokane, Yukihiro Mikumo
      Pages 178-192

    5. Soft Computing-Based Recognition of Musical Sounds

      • Bozena Kostek
      Pages 193-213

    6. Rough Sets in Industrial Applications

      • Adam Mrózek, Leszek PÅ‚onka
      Pages 214-237

    7. Rough Sets in Economic Applications

      • Adam Mrózek, Krzysztof Skabek
      Pages 238-271

    8. Multistage Rough Set Analysis of Therapeutic Experience with Acute Pancreatitis

      • Krzysztof SÅ‚owiÅ„ski, Jerzy Stefanowski
      Pages 272-294

    9. Reduction Methods for Medical Data

      • Hideo Tanaka, Yutaka Maeda
      Pages 295-306

    10. Formalization and Induction of Medical Expert System Rules Based on Rough Set Theory

      • Shusaku Tsumoto
      Pages 307-323

    11. Rough Sets for Database Marketing

      • Dirk Van den Poel
      Pages 324-335
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Keywords

About this book

The papers on rough set theory and its applications placed in this volume present a wide spectrum of problems representative to the present. stage of this theory. Researchers from many countries reveal their rec.ent results on various aspects of rough sets. The papers are not confined only to mathematical theory but also include algorithmic aspects, applications and information about software designed for data analysis based on this theory. The volume contains also list of selected publications on rough sets which can be very useful to every one engaged in research or applications in this domain and sometimes perhaps unaware of results of other authors. The book shows that rough set theory is a vivid and vigorous domain with serious results to its credit and bright perspective for future developments. It lays on the crossroads of fuzzy sets, theory of evidence, neural networks, Petri nets and many other branches of AI, logic and mathematics. These diverse connec­ tions seem to be a very fertile feature of rough set theory and have essentially contributed to its wide and rapid expansion. It is worth mentioning that its philosophical roots stretch down from Leibniz, Frege and Russell up to Popper. Therefore many concepts dwelled on in rough set theory are not entirely new, nevertheless the theory can be viewed as an independent discipline on its own rights. Rough set theory has found many interesting real life applications in medicine, banking, industry and others.

Editors and Affiliations

  • Institute of Mathematics, Warsaw University of Technology, Warsaw, Poland

    Lech Polkowski

  • Polish-Japanese Institute of Computer Techniques, Warsaw, Poland

    Lech Polkowski

  • Institute of Mathematics, Warsaw University, Warsaw, Poland

    Andrzej Skowron

Bibliographic Information

  • Book Title: Rough Sets in Knowledge Discovery 2

  • Book Subtitle: Applications, Case Studies and Software Systems

  • Editors: Lech Polkowski, Andrzej Skowron

  • Series Title: Studies in Fuzziness and Soft Computing

  • DOI: https://doi.org/10.1007/978-3-7908-1883-3

  • Publisher: Physica Heidelberg

  • eBook Packages: Springer Book Archive

  • Copyright Information: Physica-Verlag Heidelberg 1998

  • Hardcover ISBN: 978-3-7908-1120-9Published: 20 August 1998

  • Softcover ISBN: 978-3-7908-2459-9Published: 21 October 2010

  • eBook ISBN: 978-3-7908-1883-3Published: 14 March 2013

  • Series ISSN: 1434-9922

  • Series E-ISSN: 1860-0808

  • Edition Number: 1

  • Number of Pages: X, 601

  • Topics: IT in Business, Artificial Intelligence, Database Management

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