Sudipto Guha, Rajeev Rastogi, Kyuseok Shim  Home/Search
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Abstract: Clustering, in data mining, is useful for discovering groups and identifying interesting distributions in the underlying data. Traditional clustering algorithms either favor clusters with spherical shapes and similar sizes, or are very fragile in the presence of outliers. We propose a new clustering algorithm called CURE that is more robust to outliers, and identifies clusters having non-spherical shapes and wide variances in size. CURE achieves this by representing each cluster by a certain... (Update)
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BibTeX entry: (Update)
S. Guha, R. Rastogi, and K. Shim. CURE: An efficient clustering algorithm for large databases. In Proceedings of ACM SIGMOD International Conference on Management of Data, pages 73--84, New York, 1998. ACM. http://citeseer.ist.psu.edu/article/guha98cure.html More
@inproceedings{ guha98cure,
author = "Sudipto Guha and Rajeev Rastogi and Kyuseok Shim",
title = "{CURE}: an efficient clustering algorithm for large databases",
pages = "73--84",
month = {June},
booktitle = {ACM SIGMOD International Conference on Management of Data},
year = "1998",
url = {citeseer.ist.psu.edu/article/guha98cure.html} }
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