HD-Eye : Visual Clustering of High-Dimensional Data

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2002
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Hinneburg, Alexander
Wawryniuk, Markus
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Proceedings of the 2002 ACM SIGMOD international conference on Management of data - SIGMOD '02. New York, New York, USA: ACM Press, 2002, pp. 629. ISBN 1-58113-497-5. Available under: doi: 10.1145/564691.564784
Zusammenfassung

Clustering of large data bases is an important research area with a large variety of applications in the data base 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 to solve this problem since it provides effective support of different clustering paradigms and allows a visual inspection of the results. The HD-Eye (high-dim. eye) system shows that a tight integration of advanced clustering algorithms and state-of-the-art visualization techniques is powerful for a better understanding and effective guidance of the clustering process, and therefore can help to significantly improve the clustering results.

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the 2002 ACM SIGMOD international conference, 3. Juni 2002 - 6. Juni 2002, Madison, Wisconsin
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ISO 690HINNEBURG, Alexander, Daniel A. KEIM, Markus WAWRYNIUK, 2002. HD-Eye : Visual Clustering of High-Dimensional Data. the 2002 ACM SIGMOD international conference. Madison, Wisconsin, 3. Juni 2002 - 6. Juni 2002. In: Proceedings of the 2002 ACM SIGMOD international conference on Management of data - SIGMOD '02. New York, New York, USA: ACM Press, 2002, pp. 629. ISBN 1-58113-497-5. Available under: doi: 10.1145/564691.564784
BibTex
@inproceedings{Hinneburg2002HDEye-5588,
  year={2002},
  doi={10.1145/564691.564784},
  title={HD-Eye : Visual Clustering of High-Dimensional Data},
  isbn={1-58113-497-5},
  publisher={ACM Press},
  address={New York, New York, USA},
  booktitle={Proceedings of the 2002 ACM SIGMOD international conference on Management of data  - SIGMOD '02},
  author={Hinneburg, Alexander and Keim, Daniel A. and Wawryniuk, Markus}
}
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