Exploratory hot spot profile analysis using interactive visual drill-down self-organizing maps

Authors:
Denny Denny;Graham J. Williams;Peter Christen
Affiliations:
Department of Computer Science, The Australian National University, Australia and Faculty of Computer Science, University of Indonesia, Indonesia;The Australian Taxation Office and Department of Computer Science, The Australian National University, Australia;Department of Computer Science, The Australian National University, Australia
Venue:
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
Year:
2008

Citing 4
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Abstract

Real-life datasets often contain small clusters of unusual subpopulations. These clusters, or 'hot spots', are usually sparse and of special interest to an analyst. We present a methodology for identifying hot spots and ranking attributes that distinguish them interactively, using visual drill-down Self-Organizing Maps. The methodology is particularly useful for understanding hot spots in high dimensional datasets. Our approach is demonstrated using a large real life taxation dataset.