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Home > Parallel K-means Clustering Algorithm
 
Parallel K-means Clustering Algorithm
Paper Type
Opinion
Title
Parallel K-means Clustering Algorithm
Author
Sanpawat Kantabutra
Email
-
Abstract:
Despite its simplicity and its linear time, a serial K-means algorithm’s time complexity remains expensive when it is applied to a problem of large size of multidimensional vectors. In this paper the author proposes an improvement by a factor of O(K/2) where K is the number of desired clusters, by applying theories of parallel computing to the algorithm. In addition to time improvement, the parallel version of K-means algorithm also enables the algorithm to run on larger memory of multiple machines when the memory of a single machine is insufficient to solve a problem.
Start & End Page
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Received Date
1999-04-02
Accepted Date
1999-08-05
Full Text
None
Correspondence:
Author Name
Sanpawat Kantabutra - Department of Computer Science, Tufts University, Medford, Massachusetts 02155 USA.
Keyword:
Keyword
Volume
Vol.26 No.2 (DECEMBER 1999)
 




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