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Hong Kong, China
Dec. 18, 2006 to Dec. 22, 2006
ISBN: 0-7695-2702-7
pp: 638-642
Dimitris K. Tasoulis , Imperial College London, South Kensington Campus
Niall M. Adams , Imperial College London, South Kensington Campus
David J. Hand , Imperial College London, South Kensington Campus
ABSTRACT
Tools for automatically clustering streaming data are becoming increasingly important as data acquisition technology continues to advance. In this paper we present an extension of conventional kernel density clustering to a spatio-temporal setting, and also develop a novel algorithmic scheme for clustering data streams. Experimental results demonstrate both the high efficiency and other benefits of this new approach.
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CITATION
Dimitris K. Tasoulis, Niall M. Adams, David J. Hand, "Unsupervised Clustering In Streaming Data", ICDMW, 2006, 2013 IEEE 13th International Conference on Data Mining Workshops, 2013 IEEE 13th International Conference on Data Mining Workshops 2006, pp. 638-642, doi:10.1109/ICDMW.2006.165
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