Book Volume 4404 2008

Visual Data Mining

Theory, Techniques and Tools for Visual Analytics

Editors:

ISBN: 978-3-540-71079-0 (Print) 978-3-540-71080-6 (Online)

Table of contents (22 chapters)

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  1. Front Matter

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  2. Visual Data Mining: An Introduction and Overview

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      Pages 1-12

      Visual Data Mining: An Introduction and Overview

  3. Part 1 – Theory and Methodologies

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      Chapter

      Pages 13-29

      The 3DVDM Approach: A Case Study with Clickstream Data

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      Chapter

      Pages 30-45

      Form-Semantics-Function – A Framework for Designing Visual Data Representations for Visual Data Mining

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      Pages 46-59

      A Methodology for Exploring Association Models

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      Chapter

      Pages 60-75

      Visual Exploration of Frequent Itemsets and Association Rules

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      Chapter

      Pages 76-90

      Visual Analytics: Scope and Challenges

  4. Part 2 – Techniques

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      Chapter

      Pages 91-102

      Using Nested Surfaces for Visual Detection of Structures in Databases

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      Chapter

      Pages 103-122

      Visual Mining of Association Rules

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      Chapter

      Pages 123-135

      Interactive Decision Tree Construction for Interval and Taxonomical Data

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      Chapter

      Pages 136-153

      Visual Methods for Examining SVM Classifiers

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      Chapter

      Pages 154-171

      Text Visualization for Visual Text Analytics

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      Chapter

      Pages 172-195

      Visual Discovery of Network Patterns of Interaction between Attributes

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      Chapter

      Pages 196-214

      Mining Patterns for Visual Interpretation in a Multiple-Views Environment

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      Chapter

      Pages 215-235

      Using 2D Hierarchical Heavy Hitters to Investigate Binary Relationships

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      Chapter

      Pages 236-247

      Complementing Visual Data Mining with the Sound Dimension: Sonification of Time Dependent Data

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      Chapter

      Pages 248-263

      Context Visualization for Visual Data Mining

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      Chapter

      Pages 264-280

      Assisting Human Cognition in Visual Data Mining

  5. Part 3 – Tools and Applications

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      Chapter

      Pages 281-311

      Immersive Visual Data Mining: The 3DVDM Approach

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      Chapter

      Pages 312-330

      DataJewel: Integrating Visualization with Temporal Data Mining

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      Chapter

      Pages 331-366

      A Visual Data Mining Environment

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