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

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 …

With the popularity of online social networks, social relation data is becoming increasingly
important to alleviate the data sparsity and cold-start problem of the traditional recommender …

In recent years, more and more recommendation algorithm considers social information.
However, in the existing social recommendation algorithm focused on the rating prediction …

Recommender systems commonly encounter with the problems of data sparsity and cold
start. Recently, social recommendation has emerged with the rapid expansion of social …

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 …

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

Social recommender systems exploit users' social relationships to improve the
recommendation accuracy. Intuitively, a user tends to trust different subsets of her social …

Traditional recommender systems usually face data sparseness and cold-start problems. To
alleviate these problems, social recommendations use social information between users to …

To address the data sparsity problem faced by recommender systems, social network
among users is often utilized to complement rating data for improving the recommendation …