(untitled) (INTERNATIONAL JOURNAL OF MANAGEMENT & INFORMATION TECHNOLOGY, 2014)
Lots of people employ recommender systems to diminish the information overload over the internet. This leads the user in a personalized manner to hit upon interesting or helpful objects in a huge space of possible options. Amongst different techniques, Collaborative filtering recommender system has pulled off great success. But this technique pays no heed towards the social relationship of the users. This problem gave birth to the Social recommender system technology which possesses the capability to recognize users likings and preferences and their social relationships. In this paper, we present novel method where we combine collaborative filtering recommender system with social friend network to use social relationships. For this, we have made use of data related to users which provides their interests as well as their social relationship. Our method helps to find the friends with dissimilar tastes and determine the close friends amongst direct friends of targeted user which has more similar tastes. This proposed approach resulted in more precise and realistic results than traditional system.