An Analysis of the Effectiveness of Various Similarity Measures for Web Page Clustering

Authors

  • J Usharani Assistant Professor Department of Computer Science Madurai Kamaraj University College Madurai
  • K Iyakutti Professor Department of Physics and Nanotechnology SRM University Chennai India

Keywords:

Web Page Clustering, vector space model, Genetic Algorithm

Abstract

One of the prominent challenges encountered with regard to web search engines is the large number of documents retrieved by the user in response to their queries. In this regard Various solutions have been proposed in the literature .One approach is to use clustering of web documents. In this paper we propose a genetic algorithm approach for clustering of web documents and study the effectiveness of using various similarity measures in this context. This paper proposes various similarities have been employed and the cosine similarity yields better results when compared to other similarity measures.

References

A.Huang “Similarity measures for text document clustering” NZCSRS(2008)

A.Strehl,J.Ghoesh “Impact of similarity measures”

N.Oikonomakon,M.vazirginnn “A review of web document Approaches”

R.kala,A.Shukla and R.Tiwang “ A novel Approach to clustering using genetic algorithm”International journal of engineering research 2010.

U.Maulik,S.Bandyopadhyay “Genetic algorithm based clustering”

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Published

2014-12-31

How to Cite

[1]
J. Usharani and K. Iyakutti, “An Analysis of the Effectiveness of Various Similarity Measures for Web Page Clustering”, Int. J. Comp. Sci. Eng., vol. 2, no. 12, pp. 125–128, Dec. 2014.

Issue

Vol. 2 No. 12 (2014): IJCSE December Edition

Section

Research Article

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