data mining: opportunities and challenges
Chapter XX - Critical and Future Trends in Data Mining A Review of Key Data Mining Technologies/Applications
Data Mining: Opportunities and Challenges
by John Wang (ed) 
Idea Group Publishing 2003
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Visual DM is an emerging area of explorative and intelligent data analysis and mining, based on the integration of concepts from computer graphics, visualization metaphors and methods, information and scientific data visualization, visual perception, cognitive psychology, diagrammatic reasoning, visual data formatting, and 3-D collaborative virtual environments. Research and developments in the methods and techniques for visual DM have helped to identify many of the research directions in the field, including visual methods for data analysis, visual DM process models, visual reasoning and uncertainty management, visual explanations, algorithmic animation methods, perceptual and cognitive aspects, and interactivity in visual DM. Other key areas include the study of domain knowledge in visual reasoning, virtual environments, visual analysis of large DBs, collaborative exploration and model building, metrics for evaluation, generic system architectures and prototypes, and methods for visualizing semantic content (Han & Kamber, 2001).

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Data Mining(c) Opportunities and Challenges
Data Mining: Opportunities and Challenges
ISBN: 1591400511
EAN: 2147483647
Year: 2003
Pages: 194
Authors: John Wang © 2008-2017.
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