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Visual Data Mining

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Cover of 'Visual Data Mining'

Table of Contents

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    Book Overview
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    Chapter 1 Visual Data Mining: An Introduction and Overview
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    Chapter 2 The 3DVDM Approach: A Case Study with Clickstream Data
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    Chapter 3 Form-Semantics-Function – A Framework for Designing Visual Data Representations for Visual Data Mining
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    Chapter 4 A Methodology for Exploring Association Models
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    Chapter 5 Visual Exploration of Frequent Itemsets and Association Rules
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    Chapter 6 Visual Analytics: Scope and Challenges
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    Chapter 7 Using Nested Surfaces for Visual Detection of Structures in Databases
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    Chapter 8 Visual Mining of Association Rules
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    Chapter 9 Interactive Decision Tree Construction for Interval and Taxonomical Data
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    Chapter 10 Visual Methods for Examining SVM Classifiers
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    Chapter 11 Text Visualization for Visual Text Analytics
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    Chapter 12 Visual Discovery of Network Patterns of Interaction between Attributes
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    Chapter 13 Mining Patterns for Visual Interpretation in a Multiple-Views Environment
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    Chapter 14 Using 2D Hierarchical Heavy Hitters to Investigate Binary Relationships
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    Chapter 15 Complementing Visual Data Mining with the Sound Dimension: Sonification of Time Dependent Data
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    Chapter 16 Context Visualization for Visual Data Mining
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    Chapter 17 Assisting Human Cognition in Visual Data Mining
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    Chapter 18 Immersive Visual Data Mining: The 3DVDM Approach
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    Chapter 19 DataJewel: Integrating Visualization with Temporal Data Mining
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    Chapter 20 A Visual Data Mining Environment
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    Chapter 21 Integrative Visual Data Mining of Biomedical Data: Investigating Cases in Chronic Fatigue Syndrome and Acute Lymphoblastic Leukaemia
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    Chapter 22 Towards Effective Visual Data Mining with Cooperative Approaches
Overall attention for this book and its chapters
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Title
Visual Data Mining
Published by
Springer Berlin Heidelberg, January 2008
DOI 10.1007/978-3-540-71080-6
ISBNs
978-3-54-071079-0, 978-3-54-071080-6
Editors

Simeon J. Simoff, Michael H. Böhlen, Arturas Mazeika

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 1 25%
Student > Bachelor 1 25%
Unknown 2 50%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 2 50%
Unknown 2 50%