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Data Analysis and Decision Support

  • Book
  • © 2005

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Editors:
  1. Daniel Baier

    1. Institute of Business Administration and Economics, Brandenburg University of Technology Cottbus, Cottbus, Germany

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  2. Reinhold Decker

    1. Department of Business Administration and Economics, Bielefeld University, Bielefeld, Germany

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  3. Lars Schmidt-Thieme

    1. Computer Based New Media Group (CGNM), Institute for Computer Science, University of Freiburg, Freiburg, Germany

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Table of contents (36 chapters)

  1. Front Matter

    Pages I-XI
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  2. Data Analysis

    1. Optimization in Symbolic Data Analysis: Dissimilarities, Class Centers, and Clustering

      • Hans-Hermann Bock
      Pages 3-10

    2. An Efficient Branch and Bound Procedure for Restricted Principal Components Analysis

      • Wayne S. DeSarbo, Robert E. Hausman
      Pages 11-20

    3. A Tree Structured Classifier for Symbolic Class Description

      • Edwin Diday, M. Mehdi Limam, Suzanne Winsberg
      Pages 21-29

    4. A Diversity Measure for Tree-Based Classifier Ensembles

      • Eugeniusz Gatnar
      Pages 30-38

    5. Repeated Confidence Intervals in Self-Organizing Studies

      • Joachim Hartung, Guido Knapp
      Pages 39-46

    6. Fuzzy and Crisp Mahalanobis Fixed Point Clusters

      • Christian Hennig
      Pages 47-56

    7. Interpretation Aids for Multilayer Perceptron Neural Nets

      • Harald Hruschka
      Pages 57-64

    8. An Unfolding Scaling Model for Aggregated Preferential Choice Data

      • Tadashi Imaizumi
      Pages 65-72

    9. Model-Based Clustering — Discussion on Some Approaches

      • Krzysztof Jajuga
      Pages 73-81

    10. Three-Way Multidimensional Scaling: Formal Properties and Relationships Between Scaling Methods

      • Sabine Krolak-Schwerdt
      Pages 82-90

    11. Empirical Approach as a Scientific Framework for Data Analysis

      • Shizuhiko Nishisato
      Pages 91-99

    12. Asymmetric Multidimensional Scaling of Relationships Among Managers of a Firm

      • Akinori Okada, Tadashi Imaizumi, Hiroshi Inoue
      Pages 100-107

    13. Aggregation of Ordinal Judgements Based on Condorcet’s Majority Rule

      • Otto Opitz, Henning Paul
      Pages 108-112

    14. ANOVA Models with Generalized Inverses

      • Wolfgang Polasek, Shuangzhe Liu
      Pages 113-121

    15. Patterns in Search Queries

      • Nadine Schmidt-Mänz, Martina Koch
      Pages 122-129

    16. Performance Drivers for Depth-First Frequent Pattern Mining

      • Lars Schmidt-Thieme, Martin Schader
      Pages 130-140

    17. On the Performance of Algorithms for Two-Mode Hierarchical Cluster Analysis — Results from a Monte Carlo Simulation Study

      • Manfred Schwaiger, Raimund Rix
      Pages 141-148

    18. Clustering Including Dimensionality Reduction

      • Maurizio Vichi
      Pages 149-156

    19. The Number of Clusters in Market Segmentation

      • Ralf Wagner, Sören W. Scholz, Reinhold Decker
      Pages 157-176
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Keywords

About this book

It is a great privilege and pleasure to write a foreword for a book honor­ ing Wolfgang Gaul on the occasion of his sixtieth birthday. Wolfgang Gaul is currently Professor of Business Administration and Management Science and the Head of the Institute of Decision Theory and Management Science, Faculty of Economics, University of Karlsruhe (TH), Germany. He is, by any measure, one of the most distinguished and eminent scholars in the world today. Wolfgang Gaul has been instrumental in numerous leading research initia­ tives and has achieved an unprecedented level of success in facilitating com­ munication among researchers in diverse disciplines from around the world. A particularly remarkable and unique aspect of his work is that he has been a leading scholar in such diverse areas of research as graph theory and net­ work models, reliability theory, stochastic optimization, operations research, probability theory, sampling theory, cluster analysis, scaling and multivariate data analysis. His activities have been directed not only at these and other theoretical topics, but also at applications of statistical and mathematical tools to a multitude of important problems in computer science (e.g., w- mining), business research (e.g., market segmentation), management science (e.g., decision support systems) and behavioral sciences (e.g., preference mea­ surement and data mining). All of his endeavors have been accomplished at the highest level of professional excellence.

Editors and Affiliations

  • Institute of Business Administration and Economics, Brandenburg University of Technology Cottbus, Cottbus, Germany

    Daniel Baier

  • Department of Business Administration and Economics, Bielefeld University, Bielefeld, Germany

    Reinhold Decker

  • Computer Based New Media Group (CGNM), Institute for Computer Science, University of Freiburg, Freiburg, Germany

    Lars Schmidt-Thieme

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