Computational Intelligence in Data Mining

1. Front Matter

   Pages ii-vii

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2. Data Mining and Statistics

   • A. Siebes

   Pages 1-38

3. Subgroup Mining

   • W. Klösgen

   Pages 39-49

4. Possibilistic Graphical Models

   • C. Borgelt, J. Gebhardt, R. Kruse

   Pages 51-67

5. An Overview of Possibilistic Logic and its Application to Nonmonotonic Reasoning and Data Fusion

   • S. Benferhat, D. Dubois, H. Prade

   Pages 69-93

6. On the Solution of Fuzzy Equation Systems

   • H.-J. Lenz, R. Müller

   Pages 95-110

7. Learning Fuzzy Models and Potential Outliers

   • M. R. Berthold

   Pages 111-126

8. An Algorithm for Adaptive Clustering and Visualisation of Highdimensional Data Sets

   • F. Schwenker, H. A. Kestler, G. Palm

   Pages 127-140

9. Learning in Computer Soccer

   • H.-D. Burkhard

   Pages 141-151

10. Controlling Based on Stochastic Models

    • H.-J. Lenz, E. Rödel

    Pages 153-164

11. Back Matter

    Pages 165-166

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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.

• 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

• University of Udine, Italy

  Giacomo Riccia

• Otto-Von-Guericke University, Germany

  Rudolf Kruse

• Free University of Berlin, Germany

  Hanz-J. Lenz

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