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Personalized Web Recommendation Combining User-centered Collaborative Technique with URL Weighting

by Delwar Hossain Arif, A H M Sofi Ullah, K M Habibullah, Md Ali Al Mamun
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 63 - Number 2
Year of Publication: 2013
Authors: Delwar Hossain Arif, A H M Sofi Ullah, K M Habibullah, Md Ali Al Mamun
10.5120/10437-5116

Delwar Hossain Arif, A H M Sofi Ullah, K M Habibullah, Md Ali Al Mamun . Personalized Web Recommendation Combining User-centered Collaborative Technique with URL Weighting. International Journal of Computer Applications. 63, 2 ( February 2013), 13-18. DOI=10.5120/10437-5116

@article{ 10.5120/10437-5116,
author = { Delwar Hossain Arif, A H M Sofi Ullah, K M Habibullah, Md Ali Al Mamun },
title = { Personalized Web Recommendation Combining User-centered Collaborative Technique with URL Weighting },
journal = { International Journal of Computer Applications },
issue_date = { February 2013 },
volume = { 63 },
number = { 2 },
month = { February },
year = { 2013 },
issn = { 0975-8887 },
pages = { 13-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume63/number2/10437-5116/ },
doi = { 10.5120/10437-5116 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:13:06.071470+05:30
%A Delwar Hossain Arif
%A A H M Sofi Ullah
%A K M Habibullah
%A Md Ali Al Mamun
%T Personalized Web Recommendation Combining User-centered Collaborative Technique with URL Weighting
%J International Journal of Computer Applications
%@ 0975-8887
%V 63
%N 2
%P 13-18
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Web usage mining has become very popular in various business areas for learning more about the users' browsing behavior and recommending the perfect product in which the user is interested in. At present there are many systems that recommend for the users on web usage mining, but most of the systems suffer from inappropriate scalability, which would lead to very weak recommendations. In this paper we proposed a new technique that gives emphasis on page view weighting based on transaction timing and building a session pattern graph for each session. This technique provides the scope for better scalability and also provides effective number of recommendations with remarkable accuracy.

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Index Terms

Computer Science
Information Sciences

Keywords

Web usage mining URL Weighting Weighted pattern graph Recommendation score Page weight

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