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By Jeff Kent

ISBN-10: 0072261706

ISBN-13: 9780072261707

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Additional info for Visual and Spatial Analysis - Advances in Data Mining, Reasoning, and Problem Solving

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Real-time 3D Visual Report courtesy of Visual Insights. See also color plates. 2 Information discovery applications for deep analysis Visual discovery-based analysis addresses the shortcomings assumptivebased analytics by providing a rich environment to support novel discovery. Chapter 2 36 Systems supporting visual discovery are used by analysts and fi-equently combine data mining, aspects of statistics, and also predictive analytics. Visual discovery is domain specific and iterative. Information visualization improves visual discovery by enabling discoveries to often "jump" out and may lead to "why" questions.

Experiments have shown that this 26 Chapter I significantly shortened users' performance time in five different airline reservation tasks. Casner [Casner, 19911 provides an extensive argumentation for taskdriven visualization: Generalizations made about the observed usefulness of a graphic for one task are highly inappropriate since using the same graphic for different tasks often causes the usefulness of the graphic to disappear. , "line graphs are best for continuous data") are too underspecified to be useful in general..

Elaborate conceptually the general steps of a task-driven visualization approach: (1) analysis of a user task, (2) generation of equivalent perceptual tasks that can be performed more efficiently, and (3) design of accompanying graphics to support the efliciency of the perceptual task. Tip: Your elaboration should decompose these three steps to smaller substeps. Be specific and provide examples for the substeps. 11. REFERENCES Reshers, C . , Feiner, S. AlitoVisual: Rule-based design of interactive multivariate visualizations.

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Visual and Spatial Analysis - Advances in Data Mining, Reasoning, and Problem Solving by Jeff Kent

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