Computational Intelligence in Data Mining

  • Giacomo Della Riccia
  • Rudolf Kruse
  • Hanz-J. Lenz

Part of the International Centre for Mechanical Sciences book series (CISM, volume 408)

Table of contents

  1. Front Matter
    Pages ii-vii
  2. A. Siebes
    Pages 1-38
  3. W. Klösgen
    Pages 39-49
  4. C. Borgelt, J. Gebhardt, R. Kruse
    Pages 51-67
  5. H.-J. Lenz, R. Müller
    Pages 95-110
  6. M. R. Berthold
    Pages 111-126
  7. H.-D. Burkhard
    Pages 141-151
  8. H.-J. Lenz, E. Rödel
    Pages 153-164
  9. Back Matter
    Pages 165-166

About these proceedings

Introduction

The book aims to merge Computational Intelligence with Data Mining, which are both hot topics of current research and industrial development, Computational Intelligence, incorporates techniques like data fusion, uncertain reasoning, heuristic search, learning, and soft computing. Data Mining focuses on unscrambling unknown patterns or structures in very large data sets. Under the headline "Discovering Structures in Large Databases” the book starts with a unified view on ‘Data Mining and Statistics – A System Point of View’. Two special techniques follow: ‘Subgroup Mining’, and ‘Data Mining with Possibilistic Graphical Models’. "Data Fusion and Possibilistic or Fuzzy Data Analysis” is the next area of interest. An overview of possibilistic logic, nonmonotonic reasoning and data fusion is given, the coherence problem between data and non-linear fuzzy models is tackled, and outlier detection based on learning of fuzzy models is studied. In the domain of "Classification and Decomposition” adaptive clustering and visualisation of high dimensional data sets is introduced. Finally, in the section "Learning and Data Fusion” learning of special multi-agents of virtual soccer is considered. The last topic is on data fusion based on stochastic models.

Keywords

Artificial Intelligence Informatik Künstliche Intelligenz / Computer Science calculus classification clustering computational intelligence data analysis data mining databases fuzzy intelligence learning logic nonmonotonic reasoning statistics uncertain reasoning visualization

Editors and affiliations

  • Giacomo Della Riccia
    • 1
  • Rudolf Kruse
    • 2
  • Hanz-J. Lenz
    • 3
  1. 1.University of UdineItaly
  2. 2.Otto-Von-Guericke UniversityGermany
  3. 3.Free University of BerlinGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-7091-2588-5
  • Copyright Information CISM Udine 2000
  • Publisher Name Springer, Vienna
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-211-83326-1
  • Online ISBN 978-3-7091-2588-5
  • Series Print ISSN 0254-1971
  • Series Online ISSN 2309-3706
  • About this book