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13

EUROPAR
1999
Springer

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Parallel k/h-Means Clustering for Large Data Sets

13 years 8 months ago

Parallel k/h-Means Clustering for Large Data Sets

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This paper describes the realization of a parallel version of the k/h-means clustering algorithm. This is one of the basic algorithms used in a wide range of data mining tasks. We show how a database can be distributed and how the algorithm can be applied to this distributed database. The tests conducted on a network of 32 PCs showed for large data sets a nearly ideal speedup.

Kilian Stoffel, Abdelkader Belkoniene

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Added	04 Aug 2010
Updated	04 Aug 2010
Type	Conference
Year	1999
Where	EUROPAR
Authors	Kilian Stoffel, Abdelkader Belkoniene

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