Recommender systems (RSs) have been playing an increasingly important role for informed
consumption, services, and decision-making in the overloaded information era and digitized …

Recommendation systems are gaining increasing popularity in many application areas like
e-commerce, movie and music recommendations, tourism, news, advertisement, stock …

Recent advances in path-based explainable recommendation systems have attracted
increasing attention thanks to the rich information provided by knowledge graphs. Most …

Traditional music recommender systems are mainly based on users' interactions, which limit
their performance. Particularly, various kinds of content information, such as metadata and …

Traditional recommendation methods suffer from limited performance, which can be
addressed by incorporating abundant auxiliary/side information. This article focuses on a …

Recommendation systems have overcome the overload of irrelevant information by
considering users' preferences and emotional states in the fields of tourism, health, e …

Technological advances integrating emotional maturity with established IoT systems are
being examined with the emergence of the fourth industrial revolution. In this article …

An essential goal of recommendation systems is to provide users with accurate and
personalized recommendations that meet their preferences. With the rapid growth of IoT …

The design of recommendation algorithms aware of the user's context has been the subject
of great interest in the scientific community, especially in the music domain where contextual …

Context-aware recommender systems dedicated to online social networks experienced
noticeable growth in the last few years. This has led to more research being done in this …