JSM 2005 - Toronto

Abstract #302858

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 37
Type: Other
Date/Time: Sunday, August 7, 2005 : 4:00 PM to 5:50 PM
Sponsor: ASA
Abstract - #302858
Title: Visual Data Mining
Author(s): Edward J. Wegman*+
Companies: George Mason University
Address: 4400 University Dr, Fairfax, VA, 22030-4422,
Keywords: statistical graphics ; parallel coordinates ; massive data sets ; clusters
Abstract:

Data mining strategies usually are applied to opportunistically collected data and frequently focus on the discovery of structure such as clusters, bumps, trends, periodicities, associations and correlations, quantization and granularity, and other structures for which a visual data analysis is appropriate and likely to yield insight. However, data mining strategies often are applied to massive datasets where visualization may not be successful due to the limits of screen resolution, human visual system resolution, and the limits of available computational resources. In this talk, we suggest strategies for overcoming such limitations and illustrate visual data mining with examples of successful attacks on high-dimensional and large datasets.


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Revised March 2005