• Corpus ID: 37647537

Parallel K-Means Clustering with Triangle Inequality

  title={Parallel K-Means Clustering with Triangle Inequality},
  author={Rachel Krohn and Christer Karlsson and Rachel Krohn},
Clustering divides data objects into groups to minimize the variation within each group. This technique is widely used in data mining and other areas of computer science. K-means is a partitional clustering algorithm that produces a fixed number of clusters through an iterative process. The relative simplicity and obvious data parallelism of the K-means algorithm make it an excellent candidate for distributed-memory parallel optimization, particularly as datasets grow beyond the size of a… 

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