Recommender systems have become an important research field since the emergence of
the first paper on collaborative filtering in the mid-1990s. Although academic research on …

With the advent of the Internet of Things, especially the Internet of Vehicles, abundant
environmental and mobile data can be generated continuously. A personalized …

The design of recommendation algorithms aware of the user's context has been the subject
of great interest in the scientific community, especially in the music domain where contextual …

The amount of touristic and travel information existing on the Internet is overwhelming.
Recommender systems are typically used to filter irrelevant information and to provide …

Existing music recommendation systems rely on collaborative filtering or content-based
technologies to satisfy users' long-term music playing needs. Given the popularity of mobile …

In this chapter different factors that may influence Quality of Experience (QoE) in the context
of media consumption, networked services, and other electronic communication services …

Context-aware recommender system (CARS) is a highly researched and implemented way
of providing a personalized service that helps users to find their desired content. One of the …

Music listening is a very personal and situational behavior for modern people who always
carry smartphones in everyday life. Therefore, contextual information, such as user's current …

Recently, location-based services (LBSs) have been increasingly popular for people to
experience new possibilities, for example, personalized point-of-interest (POI) …

The fast growth of online communities and increasing popularity of internet-accessing smart
devices have significantly changed the way people consume and share music. As an …