e-Journal
Paper Type ![]() |
Opinion |
Title ![]() |
Parallel K-means Clustering Algorithm |
Author ![]() |
Sanpawat Kantabutra |
Email ![]() |
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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.
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Start & End Page ![]() |
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Received Date ![]() |
1999-04-02 |
Revised Date ![]() |
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Accepted Date ![]() |
1999-08-05 |
Full Text ![]() |
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Keyword ![]() |
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Volume ![]() |
Vol.26 No.2 (DECEMBER 1999) |
DOI |
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Citation |
Kantabutra S., Parallel K-means Clustering Algorithm, Chiang Mai Journal of Science, 1999; 26(2): -. |
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