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There are three kinds of clustering approaches: partitioning clustering, hierarchical clustering, and hybrid clustering in terms of cluster structures. Hierarchical clustering is more flexible than partitioning clustering but very expensive for large data sets. Hybrid clustering combines the features of hierarchical and partitioning clustering. In this paper, the authors propose a parallel hybrid clustering method which is implemented using MPI (Message Passing Interface). They run the parallel program on different numbers of computer nodes/machines and compared the results with the sequential program.
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