Visual Data Mining: Theory, Techniques and Tools for Visual Analytics

Simeon J. Simoff, Michael H. Böhlen, Arturas Mazeika (auth.), Simeon J. Simoff, Michael H. Böhlen, Arturas Mazeika (eds.)3540710795, 9783540710790

The importance of visual data mining, as a strong sub-discipline of data mining, had already been recognized in the beginning of the decade. In 2005 a panel of renowned individuals met to address the shortcomings and drawbacks of the current state of visual information processing. The need for a systematic and methodological development of visual analytics was detected.

This book aims at addressing this need. Through a collection of 21 contributions selected from more than 46 submissions, it offers a systematic presentation of the state of the art in the field. The volume is structured in three parts on theory and methodologies, techniques, and tools and applications.

Table of contents :
Front Matter….Pages –
Visual Data Mining: An Introduction and Overview….Pages 1-12
The 3DVDM Approach: A Case Study with Clickstream Data….Pages 13-29
Form-Semantics-Function – A Framework for Designing Visual Data Representations for Visual Data Mining….Pages 30-45
A Methodology for Exploring Association Models….Pages 46-59
Visual Exploration of Frequent Itemsets and Association Rules….Pages 60-75
Visual Analytics: Scope and Challenges….Pages 76-90
Using Nested Surfaces for Visual Detection of Structures in Databases….Pages 91-102
Visual Mining of Association Rules….Pages 103-122
Interactive Decision Tree Construction for Interval and Taxonomical Data….Pages 123-135
Visual Methods for Examining SVM Classifiers….Pages 136-153
Text Visualization for Visual Text Analytics….Pages 154-171
Visual Discovery of Network Patterns of Interaction between Attributes….Pages 172-195
Mining Patterns for Visual Interpretation in a Multiple-Views Environment….Pages 196-214
Using 2D Hierarchical Heavy Hitters to Investigate Binary Relationships….Pages 215-235
Complementing Visual Data Mining with the Sound Dimension: Sonification of Time Dependent Data….Pages 236-247
Context Visualization for Visual Data Mining….Pages 248-263
Assisting Human Cognition in Visual Data Mining….Pages 264-280
Immersive Visual Data Mining: The 3DVDM Approach….Pages 281-311
DataJewel: Integrating Visualization with Temporal Data Mining….Pages 312-330
A Visual Data Mining Environment….Pages 331-366
Integrative Visual Data Mining of Biomedical Data: Investigating Cases in Chronic Fatigue Syndrome and Acute Lymphoblastic Leukaemia….Pages 367-388
Towards Effective Visual Data Mining with Cooperative Approaches….Pages 389-406
Back Matter….Pages –