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