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Rough Sets in Knowledge Discovery 1

Methodology and Applications

  • Book
  • Mar 2014
  • Latest edition


  • 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 18)

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About this book

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.


  • Datenanalyse
  • Fuzzy-Logik
  • complexity
  • data analysis
  • data mining
  • data model
  • data modelling
  • database
  • decision tree
  • distributed systems
  • fuzzy logic
  • information system
  • knowledge discovery
  • learning
  • modeling

Editors and Affiliations

  • Polish-Japanese Institute of Information Technology, Warszawa, Poland

    Lech Polkowski

Bibliographic Information

  • Book Title: Rough Sets in Knowledge Discovery 1

  • Book Subtitle: Methodology and Applications

  • Editors: Lech Polkowski

  • Series Title: Studies in Fuzziness and Soft Computing

  • Publisher: Physica Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Physica-Verlag Heidelberg 1998

  • eBook ISBN: 978-3-7908-1884-0Due: 14 April 2014

  • Series ISSN: 1434-9922

  • Series E-ISSN: 1860-0808

  • Edition Number: 1

  • Number of Pages: X, 576

  • Number of Illustrations: 56 b/w illustrations

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