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Distributed document clustering algorithms: a recent survey

Distributed document clustering algorithms: a recent survey Distributed data mining paradigm is an active research area due to the enormous volume of data that are to be processed from across a wide cluster of data nodes. Document clustering algorithms are widely applied in a variety of distributed environments like peer-to-peer networks, wireless sensor networks, etc. This paper entails a comprehensive review on most of the recent that is ultimately making massive impacts on the technological realm. These algorithms are analysed based on few pivotal elements such as clustering quality, scale-up, speed-up and accuracy. Recent advances in technology have developed MapReduce-based , which show dramatic improvements in the aforementioned analytical elements. Based on the review, intelligent discussions are presented for algorithm development and implementation. Keywords: distributed document clustering; speed-up; scale-up; MapReduce. Reference to this paper should be made as follows: Judith, J.E. and Jayakumari, J. (2015) `: a recent survey', Int. J. Enterprise Network Management, Vol. 6, No. 3, pp.207­221. Biographical notes: J.E. Judith received her BE in Computer Science and Engineering from Manonmaniam Sundaranar University in 2003 and ME in Computer Science and Engineering from Karunya University in 2006. Currently, she is working as an Assistant Professor at the Department of Computer Science and Engineering http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Enterprise Network Management Inderscience Publishers

Distributed document clustering algorithms: a recent survey

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References (22)

Publisher
Inderscience Publishers
Copyright
Copyright © 2015 Inderscience Enterprises Ltd.
ISSN
1748-1252
eISSN
1748-1260
DOI
10.1504/IJENM.2015.071134
Publisher site
See Article on Publisher Site

Abstract

Distributed data mining paradigm is an active research area due to the enormous volume of data that are to be processed from across a wide cluster of data nodes. Document clustering algorithms are widely applied in a variety of distributed environments like peer-to-peer networks, wireless sensor networks, etc. This paper entails a comprehensive review on most of the recent that is ultimately making massive impacts on the technological realm. These algorithms are analysed based on few pivotal elements such as clustering quality, scale-up, speed-up and accuracy. Recent advances in technology have developed MapReduce-based , which show dramatic improvements in the aforementioned analytical elements. Based on the review, intelligent discussions are presented for algorithm development and implementation. Keywords: distributed document clustering; speed-up; scale-up; MapReduce. Reference to this paper should be made as follows: Judith, J.E. and Jayakumari, J. (2015) `: a recent survey', Int. J. Enterprise Network Management, Vol. 6, No. 3, pp.207­221. Biographical notes: J.E. Judith received her BE in Computer Science and Engineering from Manonmaniam Sundaranar University in 2003 and ME in Computer Science and Engineering from Karunya University in 2006. Currently, she is working as an Assistant Professor at the Department of Computer Science and Engineering

Journal

International Journal of Enterprise Network Management – Inderscience Publishers

Published: Jan 1, 2015

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