Parallel k/h-Means Clustering for Large Data Sets

  title={Parallel k/h-Means Clustering for Large Data Sets},
  author={Kilian Stoffel and Abdelkader Belkoniene},
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. 

From This Paper

Topics from this paper.


Publications citing this paper.


Publications referenced by this paper.
Showing 1-6 of 6 references

Knowledge Discovery in Database Terminology

Advances in Knowledge Discovery and Data Mining • 1996
View 1 Excerpt

Parallel Algorithms for Hierarchical Clustering

Parallel Computing • 1995
View 1 Excerpt

Cluster Analysis Algorithms

Helmuth Spaeth
View 1 Excerpt

Hatigan. Clustering Algorithms

A. John
View 1 Excerpt

Similar Papers

Loading similar papers…