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

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

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

上传:鱼和流氓

时间:2009-01-26

文件大小:4.19 MB

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(PDF 英文版)
by Simeon J. Simoff, Michael B?hlen, Arturas Mazeika
Hardcover: 407 pages
Publisher: Springer (August 1, 2008)
ISBN-10: 3540710795
ISBN-13: 978-3540710790

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.

Keywords:



3DVDM

SVM classifiers

VDM

assoziation mining

clustering

context visualization

data mining

decision tree

hitters

mining patterns

multiple views invironment

nested surfaces

network patterns

text visualization

visual analytics

visual data mining

visual exploration

visual interpretation

visualization


详细介绍在此:http://www.springer.com/book/978-3-540-71079-0
Tags:AnalyticsDataMiningTheoryVisual


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