Music recommender systems (MRSs) have experienced a boom in recent years, thanks to
the emergence and success of online streaming services, which nowadays make available …

In collaborative filtering recommender systems user's preferences are expressed as ratings
for items, and each additional rating extends the knowledge of the system and affects the …

With the emergence of personality computing as a new research field related to artificial
intelligence and personality psychology, we have witnessed an unprecedented proliferation …

The new user problem in recommender systems is still challenging, and there is not yet a
unique solution that can be applied in any domain or situation. In this paper we analyze …

With the emergence of online social networks and microblogging websites, user interest
mining has been an active research topic for the past few years. However, most of the …

Recommender systems (RSs) are personalized information search and discovery
applications helping users to identify and choose useful items and information. In this paper …

Crowds are a source of transmission in the COVID-19 spread. Contention and mitigation
measures have focused on reducing people's mass gathering. Such efforts have led to a …

The rapid development of IoT sensors and data provided by Social Networks has
necessitated the fast development of recommender systems as they can be used as a tool to …

Personalized recommender systems rely on knowledge of user preferences to produce
recommendations. While those preferences are often obtained from past user interactions …

In collaborative filtering recommender systems, items recommended to an active user are
selected based on the interests of users similar to him/her. Collaborative filtering systems …