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| Preface of the Scientific Editors Preface of the Project Managers 1 Symbolic Data Analysis and the SODAS Project: Purpose, History, Perspective 1.1 Introduction 1.2 Symbolic Data Tables and Symbolic Objects 1.2.1 The Input of SDA: Symbolic Data Tables, Rules and Taxonomies 1.2.2 Sources of Symbolic Data 1.2.3 Symbolic Objects 1.3 Tools and Operations for Symbolic Objects 1.4 History and Evolution of SDA 1.5 The Content of the SODAS Project 1.5.1 SDA Methods Realized in SODAS 1.5.2 An Illustrative Example 1.5.3 Overview on the SODAS Software 1.5.4 Examples for the SODAS Strategy in Applications 1.6 Philosophical Background: Concepts and Symbolic Objects 1.6.1 First- and Second-Order Individuals 1.6.2 Intent and Extent, the Two Kinds of Concepts 1.6.3 Concepts: The Four Traditions and 'Symbolic Objects' 1.7 Advantages of Using Symbolic Data Analysis 1.8 The Future Development of SODAS 2 The Classical Data Situation 2.1 Introduction 2.2 Variables as Input Data 2.3 Quantitative Variables 2.4 Qualitative Variables 2.4.1 Nominal Variables 2.4.2 Ordinal Variables and Generalized Ordinal Variables 2.5 Data Vectors and the Data Matrix 2.6 Dependent Variables 2.6.1 Logical Dependence 2.6.2 Hierarchical Dependence (Mother-Daughter) 2.6.3 Stochastic Dependence 2.7 Missing Values 3 Symbolic Data 3.1 Three Introductory Examples 3.2 Multi-Valued and Interval Variables 3.3 Modal Variables 3,4 A Synthesis of Symbolic Data Types 3.5 The Symbolic Data Array 4 Symbolic Objects 4.1 Introduction and Examples 4.2 Relations and Descriptions 4.2.1 Relations 4.2.2 Descriptions, Description Vectors and Description Sets 4.2.3 Product Relations 4,3 Events and Assertion Objects 4.4 Boolean Symbolic Objects as Triples 4.5 Modal Symbolic Objects 5 Generation of Symbolic Objects from Relational Databases 5.1 Introduction to Relational Databases 5.2 Principles of Symbolic Object Acquisition from Relational Databases 5.3 Interaction with the Database 5.3.1 Interpretation of SQL Queries …… 6 Descriptive Statistics for Symbolic Data 7 Visualizing and Editing Symbolic Objects 8 Similarity and Dissimilarity 9 Symbolic Factor Analysis 10 Discrimination: Assigning Symbolic Objects to Classes 11 Clustering Methods for Symbolic Objects 12 Symbolic Approaches for Three-way Data 13 Illustrative Benchmark Analyses 14 The SODAS Software Package Notations and Abbreviations Bibliography Addresses of Contributors to this Volume Subject Index |
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