K-means Clustering Optimization Algorithm Based on MapReduce
Authors
Zhihua Li, Xudong Song, Wenhui Zhu, Yanxia Chen
Corresponding Author
Zhihua Li
Available Online January 2015.
- DOI
- 10.2991/isci-15.2015.29How to use a DOI?
- Keywords
- Data Mining; K-means Clustering algorithm;MapReduce; Hadoop
- Abstract
Aiming at the defects of traditional K-means clustering algorithm for big data, this paper provides K-means clustering mining optimization algorithm based on big data, shows a MapReduce software architecture which is suitable for large data processing mechanism, provides an improved method for selecting initial clustering centers and puts forward a K-means algorithm optimization based on MapReduce model. The improved algorithm is applied to the coal quality analysis, the result shows that compared with traditional algorithms, the optimization algorithm improves the efficiency of the algorithm obviously, and the accuracy is also enhanced.
- Copyright
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Zhihua Li AU - Xudong Song AU - Wenhui Zhu AU - Yanxia Chen PY - 2015/01 DA - 2015/01 TI - K-means Clustering Optimization Algorithm Based on MapReduce BT - Proceedings of the 2015 International Symposium on Computers & Informatics PB - Atlantis Press SP - 198 EP - 203 SN - 2352-538X UR - https://doi.org/10.2991/isci-15.2015.29 DO - 10.2991/isci-15.2015.29 ID - Li2015/01 ER -