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An Enhancement of Clustering Technique using Support Vector Machine Classifier

by Mehajabi Sayeeda, Rachana Kamble
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 117 - Number 2
Year of Publication: 2015
Authors: Mehajabi Sayeeda, Rachana Kamble

Mehajabi Sayeeda, Rachana Kamble . An Enhancement of Clustering Technique using Support Vector Machine Classifier. International Journal of Computer Applications. 117, 2 ( May 2015), 17-22. DOI=10.5120/20526-2863

@article{ 10.5120/20526-2863,
author = { Mehajabi Sayeeda, Rachana Kamble },
title = { An Enhancement of Clustering Technique using Support Vector Machine Classifier },
journal = { International Journal of Computer Applications },
issue_date = { May 2015 },
volume = { 117 },
number = { 2 },
month = { May },
year = { 2015 },
issn = { 0975-8887 },
pages = { 17-22 },
numpages = {9},
url = { },
doi = { 10.5120/20526-2863 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T22:58:15.461945+05:30
%A Mehajabi Sayeeda
%A Rachana Kamble
%T An Enhancement of Clustering Technique using Support Vector Machine Classifier
%J International Journal of Computer Applications
%@ 0975-8887
%V 117
%N 2
%P 17-22
%D 2015
%I Foundation of Computer Science (FCS), NY, USA

Web surfing is very essential task of daily life for any professional person they search information regarding their field. But to get exact required information from ocean internet of data have become complex task. To manage files and information properly document clustering is a good approach. Clustering method divides text information into subgroup on basis of content based similarity. Document clustering reduces searching effort and fulfils human interest information looking for. It groups similar files together to minimize the search time and complexity. This paper gives new clustering method based on hybrid XNOR function to find degree of similarities within any two documents. Resultant similarity used for document clustering by applying SVM classifier for learning network. This paper introduces new method for document clustering by use of similarity matrix calculation and this matrix is passed for training SVM network for upcoming document classification. The results show the effectiveness of proposed work. In this paper, we describe the formatting guidelines for IJCA Journal Submission.

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Index Terms

Computer Science
Information Sciences


Hybrid XNOR SVM classifier learning network Document clustering similarity matrix.