© 2017

Granular-Relational Data Mining

How to Mine Relational Data in the Paradigm of Granular Computing?


Part of the Studies in Computational Intelligence book series (SCI, volume 702)

Table of contents

  1. Front Matter
    Pages i-xv
  2. Piotr Hońko
    Pages 1-6
  3. Generalized Related Set Based Approach

    1. Front Matter
      Pages 7-7
    2. Piotr Hońko
      Pages 9-19
    3. Piotr Hońko
      Pages 39-48
  4. Description Language Based Approach

    1. Front Matter
      Pages 49-49
    2. Piotr Hońko
      Pages 51-63
    3. Piotr Hońko
      Pages 83-97
    4. Piotr Hońko
      Pages 99-114
    5. Piotr Hońko
      Pages 115-116
  5. Back Matter
    Pages 117-123

About this book


This book provides two general granular computing approaches to mining relational data, the first of which uses abstract descriptions of relational objects to build their granular representation, while the second extends existing granular data mining solutions to a relational case.

Both approaches make it possible to perform and improve popular data mining tasks such as classification, clustering, and association discovery. How can different relational data mining tasks best be unified? How can the construction process of relational patterns be simplified? How can richer knowledge from relational data be discovered? All these questions can be answered in the same way: by mining relational data in the paradigm of granular computing!

This book will allow readers with previous experience in the field of relational data mining to discover the many benefits of its granular perspective. In turn, those readers familiar with the paradigm of granular computing will find valuable insights on its application to mining relational data. Lastly, the book offers all readers interested in computational intelligence in the broader sense the opportunity to deepen their understanding of the newly emerging field granular-relational data mining.


Relational Data Mining Knowledge Discovery Granular Computing Information Processing Rough Sets Rough-granular Computing Classification Association Discovery

Authors and affiliations

  1. 1.Bialystok University of TechnologyFaculty of Computer Science Bialystok University of TechnologyBiałystokPoland

Bibliographic information

  • Book Title Granular-Relational Data Mining
  • Book Subtitle How to Mine Relational Data in the Paradigm of Granular Computing?
  • Authors Piotr Hońko
  • Series Title Studies in Computational Intelligence
  • Series Abbreviated Title Studies Comp.Intelligence
  • DOI
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Engineering Engineering (R0)
  • Hardcover ISBN 978-3-319-52750-5
  • Softcover ISBN 978-3-319-84977-5
  • eBook ISBN 978-3-319-52751-2
  • Series ISSN 1860-949X
  • Series E-ISSN 1860-9503
  • Edition Number 1
  • Number of Pages XV, 123
  • Number of Illustrations 4 b/w illustrations, 0 illustrations in colour
  • Topics Computational Intelligence
    Artificial Intelligence
  • Buy this book on publisher's site
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