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Recommendation of Web Pages using Weighted K-Means Clustering

by R. Thiyagarajan, K. Thangavel, R. Rathipriya
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 86 - Number 14
Year of Publication: 2014
Authors: R. Thiyagarajan, K. Thangavel, R. Rathipriya
10.5120/15057-3517

R. Thiyagarajan, K. Thangavel, R. Rathipriya . Recommendation of Web Pages using Weighted K-Means Clustering. International Journal of Computer Applications. 86, 14 ( January 2014), 44-48. DOI=10.5120/15057-3517

@article{ 10.5120/15057-3517,
author = { R. Thiyagarajan, K. Thangavel, R. Rathipriya },
title = { Recommendation of Web Pages using Weighted K-Means Clustering },
journal = { International Journal of Computer Applications },
issue_date = { January 2014 },
volume = { 86 },
number = { 14 },
month = { January },
year = { 2014 },
issn = { 0975-8887 },
pages = { 44-48 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume86/number14/15057-3517/ },
doi = { 10.5120/15057-3517 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:04:15.467792+05:30
%A R. Thiyagarajan
%A K. Thangavel
%A R. Rathipriya
%T Recommendation of Web Pages using Weighted K-Means Clustering
%J International Journal of Computer Applications
%@ 0975-8887
%V 86
%N 14
%P 44-48
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Web Recommendation Systems are implemented by using collaborative filtering approach. It is a specific type of information filtering system that aims to predict the user browsing activity and then recommend to the user web pages items that are likely to be of interest. In this paper, a new recommendation system is proposed by using Weighted K-Means clustering approach to predict the user's navigational behavior. The proposed recommendation system based on Weighted K-Means clustering performs well when compared to K-Means algorithm. The performance of the comparative analysis is presented through experimental results.

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Index Terms

Computer Science
Information Sciences

Keywords

Web Usage Mining Web recommendation system K-Means clustering Weighted K-Means clustering Hamming distance Mean square residue.

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