Recently, recommender systems have played an increasingly important role in a wide
variety of commercial applications to help users find favourite products. Research in the …

Diversification has become one of the leading topics of recommender system research not
only as a way to solve the over-fitting problem but also an approach to increasing the quality …

Recommendation systems are ubiquitous and impact many domains; they have the potential
to influence product consumption, individuals' perceptions of the world, and life-altering …

Due to the explosion of available information on the Internet, the need for effective means of
accessing and processing them has become vital for everyone. Recommender systems …

With the emergence of online social networks, the social network-based recommendation
approach is popularly used. The major benefit of this approach is the ability of dealing with …

Online social networks play a major role in modern societies, and they have shaped the way
social relationships evolve. Link prediction in social networks has many potential …

Graph convolutions, in both their linear and neural network forms, have reached state-of-the-
art accuracy on recommender system (RecSys) benchmarks. However, recommendation …

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

Nowadays, due to the increasing amount of data, the use of recommender systems has
increased. Therefore, the quality of the recommendations for the users of these systems is …

With the abundance of information produced by users on items (eg, purchase or rating
histories), recommender systems are a major ingredient of online systems such as e-stores …