DocumentCode :
1026198
Title :
An Information-Theoretic View of Visual Analytics
Author :
Chen, Chaomei
Author_Institution :
Drexel Univ., Philadelphia
Volume :
28
Issue :
1
fYear :
2008
Firstpage :
18
Lastpage :
23
Abstract :
Visual analytics is an emerging discipline that helps connect dots. It facilitates analytical reasoning and decision making through integrated and highly interactive visualization of complex and dynamic data and situations. Solving mysteries is only part of the game. Visual analytics must augment analyst and decision-maker capabilities to assimilate complex situations and reach informed decisions. In information theory, the information value carried by a message is the difference in information entropy before and after receipt of the message. Information entropy is a macroscopic measure of uncertainty defined on a frequency or probability distribution. The information-theoretical approach attempts to quantify discrepancies of the information content of distributions.
Keywords :
data visualisation; decision making; entropy; interactive systems; probability; decision making; information entropy; information-theoretic view; interactive data visualization; macroscopic measure; probability distribution; visual analytical reasoning; Information analysis; Information entropy; Loss measurement; Measurement uncertainty; Microscopy; Probability distribution; Profitability; Q measurement; Visual analytics; Visualization; theory; visual analytics;
fLanguage :
English
Journal_Title :
Computer Graphics and Applications, IEEE
Publisher :
ieee
ISSN :
0272-1716
Type :
jour
DOI :
10.1109/MCG.2008.2
Filename :
4418745
Link To Document :
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