Recommender systems have become an essential tool to help resolve the information
overload problem in recent decades. Traditional recommender systems, however, suffer
from data sparsity and cold start problems. To address these issues, a great number of
recommendation algorithms have been proposed to leverage side information of users or
items (eg, social network and item category), demonstrating a high degree of effectiveness
in improving recommendation performance. This Research Commentary aims to provide a …