Thursday, 18th of May 2017, 12:00 – 1:00

Context-aware music recommendations

SR 2, ICT Building,
Technikerstraße 21a, 6020 Innsbruck


Martin Pichl
Research Assistant at DBIS group, University of Innsbruck


Over the last years, music consumption has changed fundamentally: people switch from private, mostly limited music collections to huge public music collections provided by music streaming platforms. Thus, the amount of available music has increased dramatically and music streaming platforms heavily rely on recommender systems to assist users in discovering music they like. Incorporating the context of users has been shown to improve the quality of recommendations. We present a context-aware track recommender system that exploits information about the current situation and musical preferences of the user. The presented approach allows to successfully leveraging interaction effects between listening histories, situational and track content information, substantially outperforming a set of baseline methods.

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