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.