Abstract
Recommender systems have been proven to be valuable means for web online users to cope with the information overload and have become one of the most powerful and popular tools in electronic commerce. In this paper we have proposed a novel algorithm to recommend items to users based on an hybrid method. First we use clustering to form the user clusters based on the similarity of users. We have taken users listening history for similarity calculation. Second we are going to find the items which are strongly associated with each other by using association rule mining. Finally we will be using these strong association rules in recommendation of items. Index Terms- Recommender system, clustering, Association Rule Mining, hybrid method
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
