Recommender systems have been proposed to exploit the potential of social network by filtering the information and offer recommendations to a user that he is predicted to like. Co...
Recommender systems, notably collaborative and hybrid information filtering approaches, vitally depend on neighborhood formation, i.e., selecting small subsets of most relevant pee...
Collaborative Filtering based on similarity suffers from a variety of problems such as sparsity and scalability. In this paper, we propose an ontological model of trust between us...
Alireza Zarghami, Soude Fazeli, Nima Dokoohaki, Mi...
Users of social networking services can connect with each other by forming communities for online interaction. Yet as the number of communities hosted by such websites grows over ...
We propose a hybridization of collaborative filtering and content based recommendation system. Attributes used for content based recommendations are assigned weights depending on ...