Recommender systems (RSs) have become an inseparable part of our everyday lives. They
help us find our favorite items to purchase, our friends on social networks, and our favorite …

In light of the emergence of deep reinforcement learning (DRL) in recommender systems
research and several fruitful results in recent years, this survey aims to provide a timely and …

In light of the emergence of deep reinforcement learning (DRL) in recommender systems
research and several fruitful results in recent years, this survey aims to provide a timely and …

Smart cities require the development of information and communication technology to
become a reality (ICT). A “smart city” is built on top of a “smart grid”. The implementation of …

Knowledge graphs have been widely adopted to improve recommendation accuracy. The
multi-hop user-item connections on knowledge graphs also endow reasoning about why an …

In this article, we study knowledge concept recommendation in Massive Open Online
Courses (MOOCs) in an explainable manner. Knowledge concepts, composing course units …

Recommender Systems (RS) play an integral role in enhancing user experiences by
providing personalized item suggestions. This survey reviews the progress in RS inclusively …

Inferring the substitutable and complementary products for a given product is an essential
and fundamental concern for the recommender system. To achieve this, existing approaches …

In recent years, machine learning technology has made great improvements in social
networks applications such as social network recommendation systems, sentiment analysis …

Sequential recommendation models aim to predict the next item based on the sequence of
items users interact with, ordered chronologically. However, these models face the …