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Text Clustering Algorithms: A Review

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International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 96 - Number 24
Year of Publication: 2014
Authors:
Himanshu Suyal
Amit Panwar
Ajit Singh Negi
10.5120/16946-7075

Himanshu Suyal, Amit Panwar and Ajit Singh Negi. Article: Text Clustering Algorithms: A Review. International Journal of Computer Applications 96(24):36-40, June 2014. Full text available. BibTeX

@article{key:article,
	author = {Himanshu Suyal and Amit Panwar and Ajit Singh Negi},
	title = {Article: Text Clustering Algorithms: A Review},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {96},
	number = {24},
	pages = {36-40},
	month = {June},
	note = {Full text available}
}

Abstract

With the growth of Internet, large amount of text data is increasing, which are created by different media like social networking sites, web, and other informatics sources, etc. This data is in unstructured format which makes it tedious to analyze it, so we need methods and algorithms which can be used with various types of text formats. Clustering is an important part of the data mining. Clustering is the process of dividing the large &similar type of text into the same class. Clustering is widely used in many applications like medical, biology, signal processing, etc. This paper briefly covers the various kinds of text clustering algorithm, present scenario of the text clustering algorithm, analysis and comparison of various aspects which contain sensitivity, stability. Algorithm contains traditional clustering like hierarchal clustering, density based clustering and self-organized map clustering.

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