K-means Clustering Optimization Algorithm Based on MapReduce

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/).

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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  -