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Review Paper: A Comparative Study on Partitioning Techniques of Clustering Algorithms

International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 87 - Number 9
Year of Publication: 2014
Gopi Gandhi
Rohit Srivastava

Gopi Gandhi and Rohit Srivastava. Article: Review Paper: A Comparative Study on Partitioning Techniques of Clustering Algorithms. International Journal of Computer Applications 87(9):10-13, February 2014. Full text available. BibTeX

	author = {Gopi Gandhi and Rohit Srivastava},
	title = {Article: Review Paper: A Comparative Study on Partitioning Techniques of Clustering Algorithms},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {87},
	number = {9},
	pages = {10-13},
	month = {February},
	note = {Full text available}


Clustering plays a vital role in research area in the field of data mining. Clustering is a process of partitioning a set of data in a meaningful sub classes called clusters. It helps users to understand the natural grouping or cluster from the data set. It is unsupervised classification that means it has no predefined classes. This paper presents a study of various partitioning techniques of clustering algorithms and their relative study by reflecting their advantages individually. Applications of cluster analysis are Economic Science, Document classification, Pattern Recognition, Image Processing, text mining. No single algorithm is efficient enough to crack problems from different fields. Hence, in this study some algorithms are presented which can be used according to one's requirement. In this paper, various well known partitioning based methods – k-means, k-medoids and Clarans – are compared. The study given here explores the behaviour of these three methods.


  • Saurabh Shah & Manmohan Singh "Comparison of A Time Efficient Modified K-mean Algorithm with K-Mean and K-Medoid algorithm", International Conference on Communication Systems and Network Technologies, 2012.
  • T. Velmurugan,and T. Santhanam, "A Survey of Partition based Clustering Algorithms in Data Mining: An Experimental Approach" An experimental approach Information. Technology. Journal, Vol, 10,No . 3 , pp478-484,2011.
  • Shalini S Singh & N C Chauhan ,"K-means v/s K-medoids: A Comparative Study", National Conference on Recent Trends in Engineering & Technology, 2011.
  • "Data Mining Concept and Techniques" ,2nd Edition, Jiawei Han, By Han Kamber.
  • Jiawei Han and Micheline Kamber, "Data MiningTechniques", Morgan Kaufmann Publishers, 2000.
  • Abhishek Patel,"New Approach for K-mean and K-medoids algorithm", International Journal of Computer Applications Technology and Research,2013.
  • A. K. Jain, M. N. Murty, and P. J. Flynn" Data clustering: a review". ACM Computing Surveys, Vol . 31No 3,pp. 264–323, 1999.