Research Article
K-means Clustering Algorithm Characteristics Differences based on Distance Measurement
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 59 - Issue 14 |
| Published: December 2012 |
| Authors: P. Indira Priya, D. K. Ghosh |
10.5120/9616-4251
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P. Indira Priya, D. K. Ghosh . K-means Clustering Algorithm Characteristics Differences based on Distance Measurement. International Journal of Computer Applications. 59, 14 (December 2012), 12-14. DOI=10.5120/9616-4251
@article{ 10.5120/9616-4251,
author = { P. Indira Priya,D. K. Ghosh },
title = { K-means Clustering Algorithm Characteristics Differences based on Distance Measurement },
journal = { International Journal of Computer Applications },
year = { 2012 },
volume = { 59 },
number = { 14 },
pages = { 12-14 },
doi = { 10.5120/9616-4251 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2012
%A P. Indira Priya
%A D. K. Ghosh
%T K-means Clustering Algorithm Characteristics Differences based on Distance Measurement%T
%J International Journal of Computer Applications
%V 59
%N 14
%P 12-14
%R 10.5120/9616-4251
%I Foundation of Computer Science (FCS), NY, USA
Abstract
A distance measure for similarity estimation based on the differences is presented through our proposed algorithm. This kind of distance measurement is implemented in the K-means clustering algorithm. In this paper, a new Minkowski distance based K-means algorithm called Enhanced K-means Clustering algorithm (EKMCA) is proposed and also demonstrates the effectiveness of the distance measurement, the performance of this kind of distance and the Euclidian and Minkowski distances were compared by clustering KDD'99 Cup dataset. Experiment results show that the new distance measure can provide a more accurate feature model than the classical Euclidean and Manhattan distances.
References
- Tingting Cui, Fangshi Li, "Weight Computing in Competitive K-Means Algorithm", IEEE, pp. 430-435, 2012.
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- Ran Vijay Singh, M. P. S Bhatia, "Data Clustering with Modified K-means Algorithm", IEEE-International Conference on Recent Trends in Information Technology, pp. 717-721, 2011.
- Yufang Liu, Shibin Xiao, Xueqiang Lv, Shuicai Shi, "Research on K-Means Text Clustering Algorithm Based on Semantic ", International Conference on Computing, Control and Industrial Engineering, pp. 124-127, 2010.
- Ge Xiufeng, Xing Changzheng, "K-means Multiple Clustering Research Based on Pseudo Parallel Genetic Algorithm", International Forum on Information Technology and Applications, pp. 30-33, 2010.
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