Novel recommendation systems in social networks

Absence of the user based recommendation system is a prevalent problem in a social network. In this paper, our work tends to model distance based group and probability based group in terms deciding recommendation dynamics. Here, we want to identify the best user who appears to be the innocent audience. In this regard, the effect of network density and preference homogeneity according to the user have been calculated. We have also used the probability function to evaluate the group of user that could be recommended.