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Title: Corresponding Author: T.veeramani, 1Research Scholar, Department of Computer Science and Engineering, Saveetha School ofEngineering, Saveetha University,Chennai Comparative Analysis for Alignment Based Document Clustering
Authors: T.Veeramani ; R. Nedunchelian
Aff: Department of Computer Science and Engineering, Saveetha School ofEngineering , Saveetha University,Chennai, Tamil Nadu, India
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Keywords: Text Mining; Clustering; K-Means Clustering; Enhanced K-Means; Weighted K-Means
Abstract:Background: Document Clustering is a technique that organizes a large quantity of unordered text Document into small number of meaning full and coherent cluster. Clustering approach facilitates the presentation of search result in more compact form and enables thematic browsing result set. Objective: The main problem of existing web search result based on poor vector representation of snippets. The Data units returned from the underlying database are normally encoded into the result page dynamically for human browsing which essential for many application such as internet comparison, shopping, and also be extracted out and assigned meaningful labels. Result: We present a clustering approach such K-Means, Weighted K-Means and Enhanced K-Means Algorithm. This method is capable of handling a variety of clustering approach based on Alignment Algorithm. Conclusion: Our Experimental result shows that the precision and result are achieved to improve the performance of clustering system is highly effective.