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Concept based clustering for descriptive document classification


S Senthamarai Kannan ,

Department of Information Technology, Thiagarajar College of Engineering, Madurai, India
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N Ramaraj

Principal, GKM Engineering College, Chennai, India
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We present an approach for improving the relevance of search results by clustering the search results obtained for a query string with the help of a Concept Clustering Algorithm. The Concept Clustering Algorithm combines common phrase discovery and latent semantic indexing techniques to separate search results into meaningful groups. It looks for meaningful phrases to use as cluster labels and then assigns documents to the labels to form groups. The labels assigned to each document cluster provide meaningful information on the various documents available under that cluster. This provides a more interactive and easier way to probe through search results and identifying the relevant documents for the users using the search engine.
How to Cite: Kannan, S.S. and Ramaraj, N., 2007. Concept based clustering for descriptive document classification. Data Science Journal, 6, pp.91–98. DOI:
Published on 07 Sep 2007.
Peer Reviewed


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