Recommender systems have become de facto tools for suggesting items that are of potential
interest to users. Predicting a user's rating on an item is the fundamental recommendation …

Social-based recommender systems have been recently proposed by incorporating social
relations of users to alleviate sparsity issue of user-to-item rating data and to improve …

Social recommender system, using social relation networks as additional input to improve
the accuracy of traditional recommender systems, has become an important research topic …

Due to their potential commercial value and the associated great research challenges,
recommender systems have been extensively studied by both academia and industry …

Recommendation plays an increasingly important role in our daily lives. Recommender
systems automatically suggest items to users that might be interesting for them. Recent …

The explosive growth of social networks in recent times has presented a powerful source of
information to be utilized as an extra source for assisting in the social recommendation …

Research of social recommendation aims at exploiting social information to improve the
quality of a recommender system. It can be further divided into two classes. Explicit social …

Although Recommender Systems have been comprehensively analyzed in the past decade,
the study of social-based recommender systems just started. In this paper, aiming at …

Matrix approximation is a common model-based approach to collaborative filtering in
recommender systems. Many relevant algorithms that fuse social contextual information …

Recommender systems (RSs) provide an effective way of alleviating the information
overload problem by selecting personalized choices. Online social networks and user …