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Visual data mining modeling techniques for the visualization of mining outcomes
Authors:Ioannis Kopanakis  Babis Theodoulidis  
Affiliation:CRIM—Center of Research in Information Management, Department of Computation, UMIST, PO Box 88, Sackville Street, ManchesterM60 1QD, UK
Abstract:The visual senses for humans have a unique status, offering a very broadband channel for information flow. Visual approaches to analysis and mining attempt to take advantage of our abilities to perceive pattern and structure in visual form and to make sense of, or interpret, what we see. Visual Data Mining techniques have proven to be of high value in exploratory data analysis and they also have a high potential for mining large databases. In this work, we try to investigate and expand the area of visual data mining by proposing new visual data mining techniques for the visualization of mining outcomes.
Keywords:Visual data mining   Databases   Association rules   Classification
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