DocumentCode :
146474
Title :
A survey of clustering techniques for big data analysis
Author :
Arora, Samarth ; Chana, Inderveer
Author_Institution :
Dept. of Comput. Sci. & Eng., Thapar Univ., Patiala, India
fYear :
2014
fDate :
25-26 Sept. 2014
Firstpage :
59
Lastpage :
65
Abstract :
With the beginning of new era data has grown rapidly not only in size but also in variety. There is a difficulty in analyzing such big data. Data mining is the technique in which useful information and hidden relationship among data is extracted. The traditional data mining approaches could not be directly implanted on big data as it faces difficulties to analyze big data. Clustering is one of the major techniques used for data mining in which mining is performed by finding out clusters having similar group of data. In this paper we have discussed some of the current big data mining clustering techniques. Comprehensive analysis of these techniques is carried out and appropriate clustering algorithm is provided.
Keywords :
Big Data; data mining; pattern clustering; Big Data analysis; clustering techniques; data mining; Algorithm design and analysis; Big data; Classification algorithms; Clustering algorithms; Data mining; Machine learning algorithms; Partitioning algorithms; Big data; Clustering Techniques; Data Mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Confluence The Next Generation Information Technology Summit (Confluence), 2014 5th International Conference -
Conference_Location :
Noida
Print_ISBN :
978-1-4799-4237-4
Type :
conf
DOI :
10.1109/CONFLUENCE.2014.6949256
Filename :
6949256
Link To Document :
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