An effective context driven recommender system for e commerce applications

The rapid growth of Information and Communication Technology (ICT) increases the amount of available data and creates information overload. To manage the information overload, Websites and e-commerce applications exploit several information filtering methods such as personalized recommender systems. The recommender system aims at selecting the desired list of products based on the interest of users. Most of the traditional recommender systems focus on learning the user preferences and features of an item from user ratings and recommending the item to a user based on the matching between the user interest and item features