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Using Projections to Visually Cluster High-Dimensional Data
March/April 2003 (vol. 5 no. 2)
pp. 14-25
Alexander Hinneburg, University of Halle
Daniel Keim, University of Constance
Markus Wawryniuk, University of Constance

The clustering of large databases is an important research area with a large variety of applications in the database context. Missing in most of the research efforts are means for guiding the clustering process and understanding the results, which is especially important for high-dimensional data. Visualization technology may help solve this problem because it provides effective support of different clustering paradigms and allows a visual inspection of the results. The HD-Eye (High-Dimensional Eye) system shows that a tight integration of advanced clustering algorithms and state-of-the-art visualization techniques is powerful enough for a better understanding and effective guidance of the clustering process, and therefore can help significantly improve the clustering results.

Index Terms:
high-dimensional data, projections, clusters, databases, search algorithms
Alexander Hinneburg, Daniel Keim, Markus Wawryniuk, "Using Projections to Visually Cluster High-Dimensional Data," Computing in Science and Engineering, vol. 5, no. 2, pp. 14-25, March-April 2003, doi:10.1109/MCISE.2003.1182958
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