@article{(Open Science Index):https://publications.waset.org/pdf/10000147,
	  title     = {A Hybrid Recommendation System Based On Association Rules},
	  author    = {Ahmed Mohammed K. Alsalama},
	  country	= {},
	  institution	= {},
	  abstract     = {Recommendation systems are widely used in
e-commerce 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 content-based 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 non-favorite items of a particular user. The proposed
framework is built upon the integration of association rules mining
and the content-based approach. The results of experiments show
that our proposed framework can provide accurate recommendations
to users.
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {9},
	  number    = {1},
	  year      = {2015},
	  pages     = {55 - 62},
	  ee        = {https://publications.waset.org/pdf/10000147},
	  url   	= {https://publications.waset.org/vol/97},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 97, 2015},