• Prateek Swamy
• M M Raghuwanshi
• A A Gholghate

Serial execution of K-means algorithm on large dataset takes more execution time and does not give accurate results. Parallel processing is one of the ways to improve the performance of K-Means algorithm. But the execution time and accuracy is largely dependent on selection of initial cluster centers. In this paper, parallel processing of K-Means is proposed using an initialization method to originate initial cluster centers. Results have shown that time taken for clustering using our proposed approach is optimized as compared to serial K-Mean approach.

Serial execution, large dataset, Parallel processing, K-Means, execution time, initial cluster centers.

"Implementation of Enhanced K-Means Algorithm using OpenMP", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.2, Issue 4, page no.1129-1134, April-2015, Available :http://www.jetir.org/papers/JETIR1504052.pdf

"Implementation of Enhanced K-Means Algorithm using OpenMP", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.2, Issue 4, page no. pp1129-1134, April-2015, Available at : http://www.jetir.org/papers/JETIR1504052.pdf