Editors:
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 4404)
Part of the book sub series: Information Systems and Applications, incl. Internet/Web, and HCI (LNISA)
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Table of contents (22 chapters)
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Front Matter
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Visual Data Mining: An Introduction and Overview
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Part 1 – Theory and Methodologies
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Part 2 – Techniques
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Part 3 – Tools and Applications
About this book
Keywords
- SVM classifiers
- association rules mining
- clusterin
- context visualizations
- data mining
- decision trees
- density surfaces
- multiple views
- pattern mining
- text visualizations
- visual analytics
- visual exploration
- visual hierarchical heavy hitters
- visual interpretation
- visualization
Bibliographic Information
Book Title: Visual Data Mining
Book Subtitle: Theory, Techniques and Tools for Visual Analytics
Editors: Simeon J. Simoff, Michael H. Böhlen, Arturas Mazeika
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-540-71080-6
Publisher: Springer Berlin, Heidelberg
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2008
eBook ISBN: 978-3-540-71080-6Published: 23 July 2008
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: X, 407
Topics: Data Mining and Knowledge Discovery, Computer Graphics, Database Management, Information Storage and Retrieval