A REVIEW ON CLUSTERING TECHNIQUES

Alagappa Institute of Skill Development & Computer Centre,Alagappa University, Karaikudi, India.15 -16 February 2017. IT Skills Show & International Conference on Advancements In Computing Resources (SSICACR-2017)

Format: Volume 5, Issue 1, No 19, 2017

Copyright: All Rights Reserved ©2017

Year of Publication: 2017

Author: C.Solaiyappan,L.Prisilla

Reference:IJCS-247

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Abstract

Data mining is the breakthrough of identifying the hidden patterns. Data mining is sorting through data to finding the patterns, anomalies and correlations within large data sets to predict outcomes. Clustering is the main task of exploratory data analysis and data mining applications. Clustering is a data mining technique used to place data elements into related groups without advance knowledge of the group definitions and it is the process of making a group of abstract objects into classes of similar objects.clusters has the creditability to pinpointing the natural groupings of cases based on a set of attributes clustering is used in various application in the real world, Such as data/text mining, voice mining,Image processing, web mining.Clustering can be done by various of algorithms such as hierarchical, partitioning, grid and density based algorithms. In this paper, a review of diversified clustering techniques in data mining is presented.

References

[1]AmandeepKaur Mann, NavneetKaur“ Survey Paper on Clustering Techniques” International Journal of Science, Engineering and Technology Research (IJSETR) April 2013 [2]PradeepRai, Shubha Singh” A Survey of Clustering Techniques” International Journal of Computer Applications,October 2010. [3] OdedMaimon, LiorRokach, “DATA MINING AND KNOWLEDGE DISCOVERY HANDBOOK”, Springer Science+BusinessMedia.Inc, pp.321-352, 2005. [4] David Pettinger and Giuseppe Di Fatta, “). “Scalability of Efficient Parallel K-Means”, IEEE/ACM International Symposium on Cluster Computing and the Grid, pp. 308-315. [5]MadjidKhalilian, FarsadZamaniBoroujeni, Norwati Mustapha, Md. NasirSulaiman,. “K-Means Divide and Conquer Clustering”, IEEE 2009, International Conference on Computer and Automation Engineering, pp. 306-309. [6] Y.-T. Kao, E. Zahara, . A hybridized approach to data clustering, Expert Systems with Applications, pp. 1754-1762. [7] Nisha and Puneet Jai Kaur, “A Survey of Clustering Techniques and Algorithms”, IEEE (978-9-3805-4415-1), 2015 [8] Anoop Kumar Jain, Prof. Satyam Maheswari, “Survey of Recent Clustering Techniques in Data Mining”, International Journal of Computer Science and Management Research (2278-733X), Vol 1 Issue1. [9] PavelBerkhin, “Survey of Clustering Data Mining Techniques”, Accrue Software, Inc. [10] Namrata S. Gupta, Bijendra S. Agrawal, Rajkumar M. Chauhan, “Survey on Clustering Techniques of Data Mining”, American International Journal of Research in Science, Technology, Engineering & Mathematics (2328-3491), 9(3), December 2014-February 2015, pp. 206-211.

Keywords

Clustering, Types of Clustering.

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