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A Imputed Neighborhood based Collaborative Filtering System for Web Personalization

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Author(s): Suresh Joseph. K | Ravichandran.T

Journal: International Journal of Computer Applications
ISSN 0975-8887

Volume: 19;
Issue: 08;
Start page: 19;
Date: 2011;
Original page

Keywords: Collaborative Filtering | Imputation Recommender Systems | Divisive Hierarchical Clustering | Web Personalization

ABSTRACT
Recommender system is the most important technology in Ecommerce .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.
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