Data Analysis and Information Systems

1. Front Matter

   Pages I-XIV

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2. Classification and Clustering

   1. Front Matter

      Pages 1-1

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   2. MDL for Mixtures of Normal Distributions

      • Peter G. Bryant

      Pages 3-14

   3. A New Algorithm for Two-Mode Clustering

      • Wolfgang Gaul, Martin Schader

      Pages 15-23

   4. Computational Methods in Clustering from a Mathematical Programming Viewpoint

      • Pierre Hansen, Brigitte Jaumard

      Pages 24-40

   5. Classification of Time Series with Optimized Time-Frequency Representations

      • Christoph Heitz

      Pages 41-51

   6. Cluster Analysis Using Spatial Autocorrelation

      • Mushtaq Hussain, Klemens Fuchs

      Pages 52-63

   7. Bounds for p-values of Combinatorial Tests for Clustering in Epidemiology

      • Joachim Krauth

      Pages 64-72

   8. Probability Distributions on Indexed Dendrograms and Related Problems of Classifiability

      • Bernard Van Cutsem, Bernard Ycart

      Pages 73-87

   9. On the Validation of Classification Trees

      • K.-D. Wernecke, K. Possinger, G. Kalb

      Pages 88-98

3. Uncertainty and Fuzziness

   1. Front Matter

      Pages 99-99

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   2. Modeling Weak Information with Generalized Basic Probability Assignments

      • Thomas Augustin

      Pages 101-113

   3. Validity Measures for Fuzzy Partitions

      • Christian Bäck, Mushtaq Hussain

      Pages 114-125

   4. Uncertainty and Actor-Oriented Information Retrieval in µ-AKCESS An Approach Based on Fuzzy Set Theory

      • Peter Mutschke

      Pages 126-138

   5. The “Combination Problem” for Probability Intervals: Necessary Assumptions

      • Sigrid Pöhlmann

      Pages 139-149

   6. A Classification System for Uncertainty Theories: How to Select an Appropriate Formalism ?

      • Elisabeth Umkehrer, Kerstin Schill

      Pages 150-159

4. Methods of Data Analysis and Applications

   1. Front Matter

      Pages 161-161

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   2. Analyzing Paired Comparisons Data Using Probabilistic Ideal Point Models and Probabilistic Vector Models

      • Daniel Baier, Wolfgang Gaul

      Pages 163-174

   3. Consensus Rules for Molecular Sequences: Open Problems

      • H. H. Bock, W. H. E. Day, F. R. McMorris

      Pages 175-185

   4. Latent Dimensions of Managers’ Risk Perception: An Application of Correspondence Analysis

      • Claudia Mennicken, Ingo Balderjahn

      Pages 186-196

This volume presents 45 articles dealing with theoretical aspects, methodo­ logical advances and practical applications in domains relating to classifica­ tion and clustering, statistical and computational data analysis, conceptual or terminological approaches for information systems, and knowledge struc­ tures for databases. These articles were selected from about 140 papers presented at the 19th Annual Conference of the Gesellschaft fur Klassifika­ tion, the German Classification Society. The conference was hosted by W. Polasek at the Institute of Statistics and Econometry of the University of 1 Basel (Switzerland) March 8-10, 1995 . The papers are grouped as follows, where the number in parentheses is the number of papers in the chapter. 1. Classification and clustering (8) 2. Uncertainty and fuzziness (5) 3. Methods of data analysis and applications (7) 4. Statistical models and methods (4) 5. Bayesian learning (5) 6. Conceptual classification, knowledge ordering and information systems (12) 7. Linguistics and dialectometry (4). These chapters are interrelated in many respects. The reader may recogni­ ze, for example, the analogies and distinctions existing among classification principles developed in such different domains as statistics and information sciences, the benefit to be gained by the comparison of conceptual and ma­ thematical approaches for structuring data and knowledge, and, finally, the wealth of practical applications described in many of the papers. For convenience of the reader, the content of this volume is briefly reviewed.

• Classification
• Datenanalyse
• Information Systems
• Informationssysteme
• Klassifikation
• Likelihood
• Normal distribution
• Probability distribution
• Time series
• calculus
• cluster analysis
• correlation
• data analysis
• inferential statistics
• statistics

• Institut für Statistik und Wirtschaftsmathematik, Rheinisch-Westfälische Technische Hochschule Aachen (RWTH), Aachen, Germany

  Hans-Hermann Bock

• Institut für Statistik und Ökonometrie, Universität Basel, Basel, Switzerland

  Wolfgang Polasek

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