Understand Customer Behavior Using Social Media in Recommendation System

With the proliferation of electronic commerce and knowledge economy environment, organizations generate and consume a large amount of online information. Because of large amount of product information on internet, customer has to face difficulty in selection of items. This difficulty can be reduced by recommendation systems [RS]. Many websites such as youtube, e-Bay and amazon have their own versions of recommendation systems, which are having some drawbacks like insufficient data, changing data, changing user preferences and uncertain items. In this paper we do literature review of collaborative filtering, content based filtering and hybrid recommendation algorithms which address issues such as insufficiency of data and change in user preference problem in e-commerce domain. In this paper we have proposed recommendation system which is integrated with social network trust. In this paper, at first a trust score is calculating using social interaction between users. Then trust based recommendation model is proposed.