Deep learning, which is a subfield of machine learning, has opened a new era for the
development of neural networks. The auto-encoder is a key component of deep structure …

In the past decade, recommender systems have been widely used to provide users with
personalized products and services. However, most traditional recommender systems are …

Generative models such as Generative Adversarial Networks (GANs) and Variational Auto-
Encoders (VAEs) are widely utilized to model the generative process of user interactions …

With the widespread popularization of social network platforms, user-generated content and
other social network data are growing rapidly. It is difficult for social users to select interested …

Nowadays, the issue of information overload is gradually gaining exposure in the Internet of
Things (IoT), calling for more research on recommender system in advance for industrial IoT …

With the increasing demand of users for personalized social services, social
recommendation (SR) has been an important concern in academia. However, current …

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 …

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

Recent years have witnessed remarkable information overload in online social networks,
and social network based approaches for recommender systems have been widely studied …