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Reseach Article

A Imputed Neighborhood based Collaborative Filtering System for Web Personalization

by Suresh Joseph. K, Ravichandran.T
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 19 - Number 8
Year of Publication: 2011
Authors: Suresh Joseph. K, Ravichandran.T
10.5120/2382-3143

Suresh Joseph. K, Ravichandran.T . A Imputed Neighborhood based Collaborative Filtering System for Web Personalization. International Journal of Computer Applications. 19, 8 ( April 2011), 19-23. DOI=10.5120/2382-3143

@article{ 10.5120/2382-3143,
author = { Suresh Joseph. K, Ravichandran.T },
title = { A Imputed Neighborhood based Collaborative Filtering System for Web Personalization },
journal = { International Journal of Computer Applications },
issue_date = { April 2011 },
volume = { 19 },
number = { 8 },
month = { April },
year = { 2011 },
issn = { 0975-8887 },
pages = { 19-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume19/number8/2382-3143/ },
doi = { 10.5120/2382-3143 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:06:28.302238+05:30
%A Suresh Joseph. K
%A Ravichandran.T
%T A Imputed Neighborhood based Collaborative Filtering System for Web Personalization
%J International Journal of Computer Applications
%@ 0975-8887
%V 19
%N 8
%P 19-23
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Recommender system is the most important technology in E-commerce .It is used to suggest valuable products for the customer and improve their business intelligence. Collaborative filtering is a technique which is used to suggest information from similar kinds of users. Scalability is the biggest challenge in collaborative filtering recommender system. When more number of users is increasing in the site the system should provide accurate recommendations for the super user. We use Imputed divisive hierarchical clustering approach to overcome this scalability issue when more number of users increases in terms of neighborhood size.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Collaborative Filtering Imputation Recommender Systems Divisive Hierarchical Clustering Web Personalization