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 …

“Nature shows us only the tail of the lion. But I do not doubt that the lion belongs to it even
though he cannot at once reveal himself because of his enormous size.”–Albert Einstein 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 …

Automated recommendations have become a ubiquitous part of today's online user
experience. These systems point us to additional items to purchase in online shops, they …

Recommender Systems are the set of tools and techniques to provide useful
recommendations and suggestions to the users to help them in the decision-making process …

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 …

Group recommendation has attracted researchers' attention in various domains, specifically
such approaches utilizing location-based social networks (LBSNs). However, point of …

Personality, as defined in psychology, accounts for the individual differences in users'
preferences and behaviour. It has been found that there are significant correlations between …

Recommender systems, in real-world circumstances, tend to limit user exposure to certain
topics and to overexpose them to others to maximize performance. However, repeated …