The advent of the Internet and the proliferation of digital services have led to a radical change in the way people enjoy radio and television. The plethora of products, services and content available on the Internet has accustomed its users to interactivity, the ability to search and choose when and what media content to listen, transforming the traditional radio and television listeners into an active consumers, capable of expressing their tastes and preferences. Paradoxically, the vast amount of content available has created an informative overhead and created the problem of finding the most suitable content for each user.
Recommender Systems represent the technological response to the need of relevance. In this context, the broadcaster has the opportunity to evolve its communicative paradigm: in addition to broadcast its content, it can propose the most relevant to its users.

Personalized Linear Radio is based on the idea of replacing part of the audio of linear radio with personalized and user-specific audio content. Audio content can be downloaded from the Internet or from other sources. The context can be the profile of the listener, her mood and activity she is doing, her position, the weather conditions, and all the factors that contribute to characterizing the listener’s status. The ultimate goal of the service is to improve listeners’ user experience, giving them targeted content, while optimizing the use of network resources.