The music domain is among the most important ones for adopting recommender systems
technology. In contrast to most other recommendation domains, which predominantly rely on …

The performance of recommender systems highly impacts both music streaming platform
users and the artists providing music. As fairness is a fundamental value of human life, there …

As recommender systems play an important role in everyday life, there is an increasing
pressure that such systems are fair. Besides serving diverse groups of users, recommenders …

The majority of music consumption nowadays takes place on music streaming platforms.
Whichever artists, albums, or songs are exposed to consumers on these platforms therefore …

In this paper, we propose a new privacy solution for the data used to train a recommender
system, ie, the user–item matrix. The user–item matrix contains implicit information, which …

Recommender Systems are a predictive model for personalized suggestions utilizing past
interactions and experiences. Collaborative filtering is the most popular and successful …

Music recommender systems, commonly integrated into streaming services, help listeners
find music. Previous research on such systems has focused on providing the best possible …

Music streaming services have become one of the main sources of music consumption in
the last decade, with recommender systems playing a crucial role. Since these systems …

Music streaming platforms nowadays play an important role in music consumption and have
a big influence on the musical taste of the listeners. Machine learning-based recommender …

In light of the COVID-19 pandemic making it difficult for people to get together in person, this
paper describes a public web service called Kiite Cafe that lets users get together virtually to …