An Analysis of the Effectiveness of Various Similarity Measures for Web Page Clustering
J.Usharani 1 , K.Iyakutti 2
Section:Research Paper, Product Type: Journal Paper
Volume-2 ,
Issue-12 , Page no. 125-127, Dec-2014
Online published on Dec 31, 2014
Copyright © J.Usharani , K.Iyakutti . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
View this paper at Google Scholar | DPI Digital Library
How to Cite this Paper
- IEEE Citation
- MLA Citation
- APA Citation
- BibTex Citation
- RIS Citation
IEEE Style Citation: J.Usharani , K.Iyakutti, “An Analysis of the Effectiveness of Various Similarity Measures for Web Page Clustering,” International Journal of Computer Sciences and Engineering, Vol.2, Issue.12, pp.125-127, 2014.
MLA Style Citation: J.Usharani , K.Iyakutti "An Analysis of the Effectiveness of Various Similarity Measures for Web Page Clustering." International Journal of Computer Sciences and Engineering 2.12 (2014): 125-127.
APA Style Citation: J.Usharani , K.Iyakutti, (2014). An Analysis of the Effectiveness of Various Similarity Measures for Web Page Clustering. International Journal of Computer Sciences and Engineering, 2(12), 125-127.
BibTex Style Citation:
@article{_2014,
author = {J.Usharani , K.Iyakutti},
title = {An Analysis of the Effectiveness of Various Similarity Measures for Web Page Clustering},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {12 2014},
volume = {2},
Issue = {12},
month = {12},
year = {2014},
issn = {2347-2693},
pages = {125-127},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=348},
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=348
TI - An Analysis of the Effectiveness of Various Similarity Measures for Web Page Clustering
T2 - International Journal of Computer Sciences and Engineering
AU - J.Usharani , K.Iyakutti
PY - 2014
DA - 2014/12/31
PB - IJCSE, Indore, INDIA
SP - 125-127
IS - 12
VL - 2
SN - 2347-2693
ER -
VIEWS | XML | |
3505 | 3238 downloads | 3519 downloads |
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.
Key-Words / Index Term
Web Page Clustering, vector space model, Genetic Algorithm
References
[1]A.Huang “Similarity measures for text document clustering” NZCSRS(2008)
[2]A.Strehl,J.Ghoesh “Impact of similarity measures”
[3]N.Oikonomakon,M.vazirginnn “A review of web document Approaches”
[4]R.kala,A.Shukla and R.Tiwang “ A novel Approach to clustering using genetic algorithm”International journal of engineering research 2010.
[5] U.Maulik,S.Bandyopadhyay “Genetic algorithm based clustering”