A mobile-based system for context-aware music recommendations

Abstract

As mobile devices are always with users and music listening is a very personal and situational behaviour, contextual information could be used to greatly enhance music recommendations. However, making such use of context, while learning user profiles, is still a challenging problem. We present a system for collecting context and usage data from mobile devices, but targeted at recommending music according to learned user profiles and specific situations. The developed data flow system requires supporting both short enough response times and longer asynchronous reasoning on the collected data. Furthermore, the mobile phone acts not only as sensor, but is directly related to the effectiveness of the music service experience. Thus, this paper provides a description of our approach to the system and the initial results of a usability test of the mobile application and its backend system. © 2012 IFIP International Federation for Information Processing.