An adaptive in-vehicle multimedia recommender for group users

Rapid advances of mobile communication technologies enable today´s vehicle to receive overabundant multimedia content from different broadcasters. In addition, the in-vehicle multimedia content is often viewed by a group of passengers traveling in buses, trains, and airplanes. Adaptive vehicular multimedia systems are required to provide personalized multimedia content for group users by taking care of the majority´s preferences. This paper proposes an adaptive in-vehicle multimedia recommendation system serving for group users. It presents the recommender system architecture. The main technologies: user identification and profile aggregation, user profile merging algorithm, and recommendation strategy are described. This paper also presents the evaluation methodology and experimental results.