A Clustering Framework for Large Document Datasets

Authors

  • Krishna Kumar Mohbey Maulana Azad National Institute of Technology Bhopal, India
  • G.S Thakur Maulana Azad National Institute of Technology Bhopal, India

Keywords:

Large Document Set, Similarity measurement, Term Extraction, Dendrogram

Abstract

Document set is the collection of different types of document. Each document contains special type of information, which is beneficial for the peoples. We have the need of document clustering by their similarity. Document may contain data related to the blogs, website access pattern, any transaction or simply text. By the clustering of similar documents one can find the future trends of the people and it is also useful for the business point of view. In this paper, we have proposed a clustering approach for large size document sets. This proposed approach immediately assign document into appropriate cluster. Experiments are conducted with the twenty newsgroup dataset using java and MATLAB software. Comparisons are also performed with the existing methods. Experimental results show the effectiveness of the proposed approach for large document sets.

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Published

2013-09-30

How to Cite

[1]
K. K. Mohbey and G. Thakur, “A Clustering Framework for Large Document Datasets”, Int. J. Comp. Sci. Eng., vol. 1, no. 1, pp. 26–30, Sep. 2013.

Issue

Vol. 1 No. 1 (2013): IJCSE September Edition

Section

Research Article

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