An Adaptive Hierarchical Clustering Algorithm for Segmenting Sentence level Text

  IJCOT-book-cover
 
International Journal of Computer & Organization Trends  (IJCOT)          
 
© 2014 by IJCOT Journal
Volume - 4 Issue - 6
Year of Publication : 2014
Authors : Gandikota Gopi , Mrs.T.Suneetha Rani
DOI : 10.14445/22492593/IJCOT-V15P310

Citation

Gandikota Gopi , Mrs.T.Suneetha Rani "An Adaptive Hierarchical Clustering Algorithm for Segmenting Sentence level Text", International Journal of Computer & organization Trends (IJCOT), V4(6):23-27 Nov - Dec 2014, ISSN:2249-2593, www.ijcotjournal.org. Published by Seventh Sense Research Group.

Abstract

Text segmentation is designed to group documents with high levels of similarity. It has found applications in several fields of text mining and data retrieval. The digital data accessible nowadays has steadily grown in tremendous volume and retrieving useful information from that is quite challenge. Text clustering has discovered an important usage to organize information and to extract useful information from the available corpus. In this proposed system , we have method for clustering the text documents. In the initial phase characteristics are choosen using a preprocessing based method. In the next phase the extracted keywords are clustered by means of hybrid algorithm.In this proosed work, graph based Fuzzy EM framework is implemented to cluster the sentences with the corpus. Experimental results show proposed approach has better performance in terms of cluster rate and time are concern

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