Visual Data Mining
Theory, Techniques and Tools for Visual Analytics
Published on 23. July 2008
X, 407 pages
978-3-540-71080-6 (ISBN)
Description
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.
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Simeon Simoff | Michael H. Böhlen | Arturas Mazeika
Visual Data Mining
Theory, Techniques and Tools for Visual Analytics
Book
07/2008
Springer
€85.59
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Content
Visual Data Mining: An Introduction and Overview.- Visual Data Mining: An Introduction and Overview.- 1 - Theory and Methodologies.- The 3DVDM Approach: A Case Study with Clickstream Data.- Form-Semantics-Function - A Framework for Designing Visual Data Representations for Visual Data Mining.- A Methodology for Exploring Association Models.- Visual Exploration of Frequent Itemsets and Association Rules.- Visual Analytics: Scope and Challenges.- 2 - Techniques.- Using Nested Surfaces for Visual Detection of Structures in Databases.- Visual Mining of Association Rules.- Interactive Decision Tree Construction for Interval and Taxonomical Data.- Visual Methods for Examining SVM Classifiers.- Text Visualization for Visual Text Analytics.- Visual Discovery of Network Patterns of Interaction between Attributes.- Mining Patterns for Visual Interpretation in a Multiple-Views Environment.- Using 2D Hierarchical Heavy Hitters to Investigate Binary Relationships.- Complementing Visual Data Mining with the Sound Dimension: Sonification of Time Dependent Data.- Context Visualization for Visual Data Mining.- Assisting Human Cognition in Visual Data Mining.- 3 - Tools and Applications.- Immersive Visual Data Mining: The 3DVDM Approach.- DataJewel: Integrating Visualization with Temporal Data Mining.- A Visual Data Mining Environment.- Integrative Visual Data Mining of Biomedical Data: Investigating Cases in Chronic Fatigue Syndrome and Acute Lymphoblastic Leukaemia.- Towards Effective Visual Data Mining with Cooperative Approaches.
