K-means Clustering - A Survey on Various Clustering Techniques

International Journal of Computer Science (IJCS Journal) Published by SK Research Group of Companies (SKRGC) Scholarly Peer Reviewed Research Journals

Format: Volume 3, Issue 2, No 2, 2015.

Copyright: All Rights Reserved ©2015

Year of Publication: 2015

Author: A. Roslin Deepa,Dr. Ramalingam Sugumar

Reference:IJCS-105

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Abstract

Clustering refers to the division of data into groups of similar objects. Each group, or cluster, consists of objects that are similar to one another and dissimilar to objects in other groups. When representing a quantity of data with a relatively small number of clusters, we achieve some simplification, at the price of some loss of detail as in lossy data compression. Clustering is a form of data modeling, which puts it in a historical perspective rooted in mathematics and statistics. Clustering is the subject of active research in several fields such as statistics, pattern recognition, and machine learning. This survey focuses on clustering in data mining. Data mining adds to clustering the complications of very large datasets with very many attributes of different types. This imposes unique computational requirements on relevant clustering algorithms. A variety of algorithms have recently emerged that meet these requirements and were successfully applied to real-life data mining problems.

References

1) Recent Advances in Clustering: A Brief Survey S.B. KOTSIANTIS, P. E. PINTELAS Department of Mathematics University of Patras Educational Software Development Laboratory Hellas {sotos, pintelas}@math.upatras.gr 2) A Survey on Clustering Techniques in Medical Diagnosis N.S.Nithya1, Dr.K.Duraiswamy2, P.Gomathy3 International Journal of Computer Science Trends and Technology (IJCST) – Volume1 Issue2, Nov-Dec 2013. 3) Density Based k-Nearest Neighbors Clustering Algorithm for Trajectory Data Ajaya K. Akasapu1, P. Srinivasa Rao2, L. K. Sharma3, S. K. Satpathy3 International Journal of Advanced Science and Technology Vol. 31, June, 2011.4) A Survey on Density Based Clustering Algorithms for Mining Large Spatial Databases M.Parimala, Daphne Lopez, N.C. Senthilkumar International Journal of Advanced Science and Technology Vol. 31, June, 2011. 5) APPROXIMATE K-NEAREST NEIGHBOUR BASED SPATIAL CLUSTERING USING K-D TREE Dr. Mohammed Otair International Journal of Database Management Systems ( IJDMS ) Vol.5, No.1, February 2013. 6) Survey of Recent Clustering Techniques in Data Mining International Archive of Applied Sciences and Technology Volume 3 [2] June 2012: 68 – 75 ISSN: 0976-4828 ©Society of Education, India Website: www.soeagra.com/iaast/iaast.htm. 7) A Survey on Target Tracking Techniques in Wireless Sensor Networks K. Ramya1, K. Praveen Kumar2, and Dr. V. Srinivas Rao3 International Journal of Computer Science & Engineering Survey (IJCSES) Vol.3, No.4, August 2012. 8) Indexing, Query Processing, and Clustering of Spatio-Temporal Text Objects Anders Skovsgaard PhD Dissertation Department of Computer Science Aarhus University, Denmark. 9) Survey of Clustering Data Mining Techniques Pavel Berkhin Accrue Software, Inc. 10) A Survey on Location Based Services in Data Mining Ipsa Das, Md Imran Alam, Jayanti Dansana International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Volume-4, Issue-2, May 2014. 11) ALGORITHMS FOR MULTI-POINT RANGE QUERY AND REVERSE NEAREST NEIGHBOUR SEARCH NG HOONG KEE (M. IT, UKM) (B. IT, USQ) A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF COMPUTER SCIENCE NATIONAL UNIVERSITY OF SINGAPORE, 2009. 12) P-DBSCAN: A density based clustering algorithm for exploration and analysis of attractive areas using collections of geo-tagged photos Slava Kisilevich, Florian Mansmann , Daniel Keim, University of Konstanz. 13) An Improved Classification of Network Traffic Using Adaptive Nearest Cluster Based Classifier D.Thuthi Sarabai., M.Sc.,M.Phil1 ,R. Krissna Priya MCA, (M.Phil)2 International Journal of Computer Trends and Technology (IJCTT) – Volume 19 Number 1 – Jan 2015. 14) Recent Trends in Users’ Query Clustering Sami Uddin , Amit kumar Nandandwar CSE Department VNS College, Bhopal, India Sami Uddin et al, / (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 5 (5) , 2014, 6744-6749 ISSN:0975-9646. 15) Clustering Data Stream for Point Density with Mobile Agent Monali Patil, Vidya Chitre, Dipti Patil International Journal of Engineering Research & Technology (IJERT) Vol. 1 Issue 4, June – 2012 ISSN:2278-0181. 16) Survey on Hierarchical Document Clustering Techniques Fihc & F2 Ihc Ms. Devika Deshmukh1 , Mr. Sandip Kamble 2 Mrs. Pranali Dandekar3 International Journal of Advanced Research in Computer Science and Software Engineering Volume 3, Issue 7, July 2013 ISSN: 2277 128X www.ijarcsse.com. 17) A Survey on Various Clustering Techniques with K-means Clustering Algorithm in Detail Supreet Kaur1, Usvir Kaur2 International Journal of Computer Science and Mobile Computing A Monthly Journal of Computer Science and Information Technology ISSN 2320–088X IJCSMC, Vol. 2, Issue. 4, April 2013, pg.155 – 159www.ijcsmc.com


Keywords

Algorithms, Design, Clustering, k-means,Cluster, Location Based Services.

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