Deep learning (DL), a branch of machine learning (ML) and artificial intelligence (AI) is
nowadays considered as a core technology of today's Fourth Industrial Revolution (4IR or …

Recommender systems have significantly developed in recent years in parallel with the
witnessed advancements in both internet of things (IoT) and artificial intelligence (AI) …

Recommendation systems are information filtering tools that present items to users based on
their preferences and behavior, for example, suggestions about scientific papers or music a …

In recent years, the use of recommender systems has become popular on the web. To
improve recommendation performance, usage, and scalability, the research has evolved by …

Recommender systems have become exceptionally widespread in recent years to deal with
the information overload problem by providing personalized recommendations. Multi-criteria …

Nowadays, various recommender systems are popular and their main aim is to recommend
suitable content to the user based on various parameters. This article proposes a hybrid …

Deep learning (DL) techniques have been widely used in recommender systems for user
modeling and matching function learning based on historical interaction matrix. However …

Matrix Factorization is a successful approach for generating an effective recommender
system. However, most existing matrix factorization methods suffer from the sparsity and cold …

With the recent development of online transactions, recommender systems have
increasingly attracted attention in various domains. The recommender system supports the …

Recommender systems attempt to provide effective suggestions to each user based on their
interests and behaviors. These recommendations usually match the personal user …