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 …

Like in many other research areas, deep learning (DL) is increasingly adopted in music
recommender systems (MRS). Deep neural networks are used in this area particularly for …

The most common way to listen to recorded music nowadays is via streaming platforms,
which provide access to tens of millions of tracks. To assist users in effectively browsing …

This chapter studies state-of-the-art research related to multimedia recommender systems
(MMRS), focusing on methods that integrate multimedia content as side information to …

I am delighted to be in a position to write this preface: it is the last task that I need to get done
before I submit the manuscript for production. I have just gone through the checklist. All good …

As of today, most movie recommendation services base their recommendations on
collaborative filtering (CF) and/or content-based filtering (CBF) models that use metadata …

This chapter gives an introduction to music recommender systems, considering the unique
characteristics of the music domain. We take a user-centric perspective, by organizing our …

We propose a multi-modal content-based movie recommender system that replaces human-
generated metadata with content descriptions automatically extracted from the visual and …

The particularities of musical data and its multiple modalities make original contributions
possible in many core RecSys topics such as content-based and hybrid recommendation …

Singing voice detection or vocal detection is a classification task that determines whether
there is a singing voice in a given audio segment. This process is a crucial preprocessing …