Recommender systems with social networks have been well studied in recent years.
However, most of these methods ignore the social contextual information among users and …

Exponential growth of information generated by social networks requires efficient and
scalable recommendation techniques to produce useful results. Traditional methods have …

Online social platforms have provided a large amount of available information to
recommendation systems. With this intuition, social recommendation systems emerged and …

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 …

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 …

This paper is concerned with how to make efficient use of social information to improve
recommendations. Most existing social recommender systems assume people share similar …

Recommender systems with social networks (RSSN) have been well studied in recent
works. However, these methods ignore the relationships among items, which may affect the …

Social recommendation has been an active research topic over the last decade, based on
the assumption that social information from friendship networks is beneficial for improving …

Attention is the behavioral and cognitive process of selectively concentrating on small
fraction of information while ignoring other perceivable information. Thus, user's attention …

Social recommendation becomes a current research focus, which leverages social relations
among users to alleviate data sparsity and cold-start problems in recommender systems …