Parallel k/h-Means Clustering for Large Data Sets

@inproceedings{Stoffel1999ParallelKC,
  title={Parallel k/h-Means Clustering for Large Data Sets},
  author={Kilian Stoffel and Abdelkader Belkoniene},
  booktitle={Euro-Par},
  year={1999}
}
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. 

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