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An Integrated Approach and Framework for Document Clustering Using Graph Based Association Rule Mining

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 236)

Abstract

Growth in number of documents increases day by day, and for managing this growth the document clustering techniques are used document clustering is a significant tool to allocating web search engines for data mining and knowledge discovery. In this paper, we have introduced a new framework graph-based frequent Term set for document clustering (GBFTDC). In this study, document clustering has been performed for extraction of useful information from document dataset based on frequent term set. We have generated association rules to perform pre-processing and then have applied clustering approach.

Keywords

Document clustering Text document Association rule  Pre-processing 

Notes

Acknowledgments

This work is supported by research grant from MANIT, Bhopal, India under Grants in Aid Scheme 2010-11, No. Dean(R&C)/2010/63 dated 31/08/2010.

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Copyright information

© Springer India 2014

Authors and Affiliations

  1. 1.Department of Computer ApplicationsM.A.N.I.T.BhopalIndia

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