2014International Journal of Computer ApplicationsOpen access

Text Clustering Algorithms: A Review

Himanshu Suyal, Amit Panwar, Ajit Singh Negi

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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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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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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.

Key concepts: Cluster analysis, Computer science, CURE data clustering algorithm, Data mining, Correlation clustering, Canopy clustering algorithm, Clustering high-dimensional data, Fuzzy clustering

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