Evaluating music recommender systems is a highly repetitive, yet non-trivial, task. But it has the advantage over other domains that recommended songs can be evaluated immediately by just listening to them. In this paper, we present MUSE ‐ a music recommendation management system ‐ for solving the typical tasks of an in vivo evaluation. MUSE provides the typical offthe-shelf evaluation algorithms, offers an online evaluation system with automatic reporting, and by integrating online streaming services also a legal possibility to evaluate the quality of recommended songs in real time. Finally, it has a built-in user management system that conforms with state-of-the-art privacy standards. New recommender algorithms can be plugged in comfortably and evaluations can be configured and managed online.
['Martin Przyjaciel-Zablocki', 'Thomas Hornung', 'Alexander Schätzle', 'Sven Gauß', 'Io Taxidou', 'Georg Lausen']
MUSE: A MUSIC RECOMMENDATION MANAGEMENT SYSTEM