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A Frequent Concepts Based Document Clustering Algorithm

International Journal of Computer Applications
© 2010 by IJCA Journal
Number 5 - Article 2
Year of Publication: 2010
Rekha Baghel
DR.Renu Dhir

Dr.Renu Dhir and Rekha Baghel. Article: A Frequent Concepts Based Document Clustering Algorithm. International Journal of Computer Applications 4(5):6–12, July 2010. Published By Foundation of Computer Science. BibTeX

	author = {Dr.Renu Dhir and Rekha Baghel},
	title = {Article: A Frequent Concepts Based Document Clustering Algorithm},
	journal = {International Journal of Computer Applications},
	year = {2010},
	volume = {4},
	number = {5},
	pages = {6--12},
	month = {July},
	note = {Published By Foundation of Computer Science}


This paper presents a novel technique of document clustering based on frequent concepts. The proposed technique, FCDC (Frequent Concepts based document clustering), a clustering algorithm works with frequent concepts rather than frequent items used in traditional text mining techniques. Many well known clustering algorithms deal with documents as bag of words and ignore the important relationships between words like synonyms. the proposed FCDC algorithm utilizes the semantic relationship between words to create concepts. It exploits the WordNet ontology in turn to create low dimensional feature vector which allows us to develop a efficient clustering algorithm. It uses a hierarchical approach to cluster text documents having common concepts. FCDC found more accurate, scalable and effective when compared with existing clustering algorithms like Bisecting K-means , UPGMA and FIHC.


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