A Survey on Various Information Clustering Approaches For Efficient Clustering Analysis
DOI:
https://doi.org/10.26438/ijcse/v6i11.628631Keywords:
Clustering, Partition clustering, Heirarchial clustering, Density based clustering, Grid based clusteringAbstract
Clustering is the way toward making a gathering of conceptual items into classes of comparable items. The primary favorable position of bunching over arrangement is that it is versatile to changes and helps single out valuable highlights that recognize diverse gatherings. The real necessities of bunching calculations are Scalability, Ability to manage various types of traits, Discovery of groups with property shape, High dimensionality, Ability to manage uproarious information, Interpretability. The point of the present work is to direct a review on ordinarily utilized grouping approaches alongside its applications
References
[1] K. Chitra & Dr. D.Maheswari,” A Comparative Study of Various Clustering Algorithms in Data Mining”, IJCSMC, Vol. 6, Issue. 8, August 2017.
[2] Han, J. and Kamber, M. Data Mining- Concepts and Techniques, 3rd Edition, 2012, Morgan Kauffman Publishers..
[3] P.Nagpal & P.Mann,” Comparative Study of Density based Clustering Algorithms”, International Journal of Computer Applications (0975 – 8887) Volume 27– No.11, August 2011
[4] Han, J. and Kamber, M. Data Mining- Concepts and Techniques, 3rd Edition, 2012, Morgan Kauffman Publishers.
[5] Bo Wu.” A Fast Density and Grid Based Clustering Method for Data with Arbitrary Shapes and Noise”, IEEE,2010.
[6] R. Elankavi, R. Kalaiprasath & R. Udayakumar,” Fast Clustering Algorithm For High-Dimensional Data”. International Journal of Civil Engineering and Technology (IJCIET) Volume 8, Issue 5, May 2017.
[7] X.Wu, H.Jiang and C.Chen,” SCMDOT: Spatial Clustering with Multiple Density-Ordered Trees”. International Journal of Geo-Information, May 2017.
[8] Ishwank Singh , A Sai Sabitha & Abhay Bansal ,” Student Performance Analysis Using Clustering Algorithm”,Ieee 2016
[9] Nelofar Rehman,” Data Mining Techniques Methods Algorithms and Tools”, IJCSMC, Vol. 6, Issue. 7, July 2017, pg.227 – 231
[10] I.A.Venkatkumar & S.J.K Shardaben ,” Comparative study of Data Mining Clustering algorithms”,IEEE,2016
[11] G.Thangaraju , J.Umarani & Dr.V.Poongodi,” Comparative Study of Clustering Algorithms: Filtered Clustering and K-Means Cluttering Algorithm Using WEKA” , International Journal of Innovative Research in Computer and Communication Engineering, Vol. 5, Issue 9, September 2017 .
[12] T. Velmurugan & T. Santhanam,” A Survey of Partition based Clustering Algorithms in Data Mining: An Experimental Approach”. Information Technology Journal Volume 10 (3): 478-484, 2011.
[13] J.Yadav & M.Sharma,” A Review of K-mean Algorithm”, International Journal of Engineering Trends and Technology (IJETT) – Volume 4 Issue 7- July 2013.
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