Ahmed Mohammed K. Alsalama
A Hybrid Recommendation System Based On Association Rules
55 - 62
2015
9
1
International Journal of Computer and Information Engineering
https://publications.waset.org/pdf/10000147
https://publications.waset.org/vol/97
World Academy of Science, Engineering and Technology
Recommendation systems are widely used in
ecommerce applications. The engine of a current recommendation
system recommends items to a particular user based on user
preferences and previous high ratings. Various recommendation
schemes such as collaborative filtering and contentbased approaches
are used to build a recommendation system. Most of current
recommendation systems were developed to fit a certain domain such
as books, articles, and movies. We propose1 a hybrid framework
recommendation system to be applied on two dimensional spaces
(User × Item) with a large number of Users and a small number
of Items. Moreover, our proposed framework makes use of both
favorite and nonfavorite items of a particular user. The proposed
framework is built upon the integration of association rules mining
and the contentbased approach. The results of experiments show
that our proposed framework can provide accurate recommendations
to users.
Open Science Index 97, 2015