Overview and New Challenges of Music Recommendation Research in 2018

Speakers: Markus Schedl, Peter Knees, Fabien Gouyon

Abstract: The current revolution in the music industry represents great opportunities and challenges for music recommendation systems. Recommendation systems are now central to music streaming platforms, which are rapidly increasing in listenership and becoming the top source of revenue for the music industry. It is increasingly more common for a music listener to simply access music than to purchase and own it in a personal collection. In this scenario, recommendation calls no longer for a one-shot recommendation for the purpose of a track or album purchase, but for a recommendation of a listening experience, comprising a very wide range of challenges, such as sequential recommendation, or conversational and contextual recommendations. Recommendation technologies now impact all actors in the rich and complex music industry ecosystem (listeners, labels, music makers and producers, concert halls, advertisers, etc.).

To acknowledge these developments, we give an introductory tutorial providing an overview of music recommendation research, as well as the challenges it faces today. We focus on three use cases: automatic playlist generation, context-aware music recommendation, and recommendation in the creative process of music making.

Materials for the tutorial: Link

Markus Schedl is an Associate Professor at the Johannes Kepler University Linz / Department of Computational Perception. He graduated in Computer Science from the Vienna University of Technology and earned his Ph.D. from the Johannes Kepler University Linz. Markus further studied International Business Administration at the Vienna University of Economics and Business Administration as well as at the Handelshögskolan of the University of Gothenburg, which led to a Master's degree. His main research interests include web and social media mining, information retrieval, multimedia, and music information research. He has been an active member of the MIR community since 14 years and since then co-authored almost 200 peer-reviewed research articles.
Peter Knees is Assistant Professor of the Faculty of Informatics, TU Wien, Austria. For over a decade he has been an active member of the ISMIR community, reaching out to the related areas of multimedia, text IR, and recommender systems. Apart from serving on the program committees of major conferences in the field, he has organized several workshops on topics of media retrieval. He is an experienced teacher of graduate-level courses on recommender systems and information retrieval and has given tutorials on music information retrieval at RecSys, SIGIR, ECIR, RuSSIR, and the Indonesian Summer School on MIR.
The presenter Peter Knees was supported by the Austrian Research Promotion Agency (FFG) under Bridge 1 grant number 858514 (SmarterJam).
Fabien Gouyon is Principal Scientist at the music streaming service Pandora, where he does applied research on personalized music recommendation, and works with the Music Genome Project. Before joining Pandora, he received a PhD in Computer Science while working in the Music Technology Group in the University Pompeu Fabra in Barcelona, and was a co-founder of Barcelona Music and Audio Technologies (BMAT), worked in the Austrian Research Institute for Artificial Intelligence in Vienna, and started and led the Sound and Music Computing Group while teaching at the University of Porto. He was President of ISMIR in 2016-2017.

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