Recommender systems have become a popular and effective means to manage the ever-
increasing amount of multimedia content available today and to help users discover …

Recommender systems are one of the most successful applications of data mining and
machine-learning technology in practice. Academic research in the field is historically often …

Session-based recommendation, which aims to predict the user's immediate next action
based on anonymous sessions, is a key task in many online services (eg, e-commerce …

Deep learning methods have led to substantial progress in various application fields of AI,
and in recent years a number of proposals were made to improve recommender systems …

Recommender systems help users find relevant items of interest, for example on e-
commerce or media streaming sites. Most academic research is concerned with approaches …

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 …

Recurrent Neural Networks are powerful tools for modeling sequences. They are flexibly
extensible and can incorporate various kinds of information including temporal order. These …

Recommender systems play an important role in providing an engaging experience on
online music streaming services. However, the musical domain presents distinctive …

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 …

Session-based recommendation becomes a research hotspot for its ability to make
recommendations for anonymous users. However, existing session-based methods have …