@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}, }