A personalized social network based cross domain recommender system

Abstract

In the last few years recommender systems has become one of the most popular research field. Although with time various new algorithms have been introduced for improving recommendations but there are some areas in this research field that still need to be concentrated on. Cross domain recommendations and recommender systems and social networks are two of the research challenges that need to be explored more. In this paper we have proposed a novel idea for making recommendations in one domain using information from the other domain. The information has been extracted from popular social networking site Facebook.com. The proposed approach has been successful in providing good recommendations.