Deep neural networks have been extensively employed in many applications such as
natural language processing and computer vision. They have attracted a lot of attention in …

Recommender systems (RSs) are programs that apply knowledge discovery techniques to
make personalized recommendations for user's information on the web. In online sharing …

Recommender systems are popular tools used in many applications, such as e-commerce, e-
learning, and social networks to help users select their desired items. Collaborative filtering …

Recommender systems (RSs) have been employed for many real-world applications
including search engines, social networks, and information retrieval systems as powerful …

Many trust-aware recommender systems have explored the value of explicit trust, which is
specified by users with binary values and simply treated as a concept with a single aspect …

Users' trust relations have a significant influence on their choice towards different products.
However, few recommendation or prediction algorithms both consider users' social trust …

Deep learning is the most active research topic amongst data scientists and analysts these
days. It is because deep learning has provided very high accuracy in various domains such …

There are two key characteristics of users in trust relationships that have been well
studied:(1) users trust their friends with different trust strengths and (2) users play multiple …

Unlike in general recommendation scenarios where a user has only a single role, users in
trust rating network, eg Epinions, are associated with two different roles simultaneously: as a …

Trust has been used to replace or complement rating-based similarity in recommender
systems, to improve the accuracy of rating prediction. However, people trusting each other …