Recommender systems can strongly influence which information we see online, eg, on
social media, and thus impact our beliefs, decisions, and actions. At the same time, these …

Recommender systems (RSs) have been playing an increasingly important role for informed
consumption, services, and decision-making in the overloaded information era and digitized …

As one of the most pervasive applications of machine learning, recommender systems are
playing an important role on assisting human decision-making. The satisfaction of users and …

The people who make music recommender systems have lofty goals: they want to broaden
listeners' horizons and help obscure musicians find audiences, taking advantage of the …

Explainable recommendation attempts to develop models that generate not only high-quality
recommendations but also intuitive explanations. The explanations may either be post-hoc …

Heterogeneous information network (HIN) has been widely adopted in recommender
systems due to its excellence in modeling complex context information. Although existing …

Data science is an interdisciplinary field that extracts knowledge and insights from many
structural and unstructured data, using scientific methods, data mining techniques, machine …

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 …

Social media platforms moderate content for each user by incorporating the outputs of both
platform-wide content moderation systems and, in some cases, user-configured personal …

Although recommender systems (RSs) play a crucial role in our society, previous studies
have revealed that the performance of RSs may considerably differ between groups of …