Overview
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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About this book
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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Keywords
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
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