Collaborative book recommendation system using trust based social network and association rule mining
Anand Shanker Tewari, Asim Gopal Barman · 2016
Almost all e-commerce websites generates recommendations for their users but most of them are irrelevant. Collaborative filtering is one of the most widely used recommendation generation technique by e-commerce websites. Collaborative filtering generates recommendations for the target user from the collaboration of the other users who have the similar interest derived from their ratings. With the advent of the Web 2.0, web based social networks have become one of the major source of information. Users can now make friends, share thoughts, images etc. on the Internet and express different level of trust on their web friends. Recommendations generated by the trusted friends are more relevant than other users. This paper propose a book recommendation system that generates recommendations from the collaboration of trusted friends of the target user and uses association rule mining to capture current reading trend of users in the network.