This paper reviews the research trends that link the advanced technical aspects of
recommendation systems that are used in various service areas and the business aspects of …

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 …

Recommender systems have been in existence everywhere with most of them using single
ratings in prediction. However, multi-criteria predictions have been proved to be more …

Recommender systems have been researched extensively over the past decades. Whereas
several algorithms have been developed and deployed in various application domains …

Existing content-based music recommendation systems typically employ a\textit {two-stage}
approach. They first extract traditional audio content features such as Mel-frequency cepstral …

We present Essentia 2.0, an open-source C++ library for audio analysis and audio-based
music information retrieval released under the Affero GPL license. It contains an extensive …

This chapter gives an introduction to music recommender systems research. We highlight
the distinctive characteristics of music, as compared to other kinds of media. We then …

We provide a survey of the field of Music Information Retrieval (MIR), in particular paying
attention to latest developments, such as semantic auto-tagging and user-centric retrieval …

Recommender systems are software tools and techniques for suggesting items in an
automated fashion to users tailored their preferences. Collaborative Filtering (CF) …

Music has long been recognised to be able to alter people's emotions and behaviours, yet
how university students use music for learning and well-being is largely unexplored. With …