Search & Recommendations

Search & recommendations research at Spotify focuses on identifying ways to provide users with seamless access to their favorite audio content, from music to podcasts, and to help them explore their taste. A big focus is on building highly effective, personalized and interactive models that exploit contextual information and historical user interactions. Our research interests include large-scale recommendation algorithms for music and more generally audio discovery, algorithms for audio search through voice and text, query analysis for effective query suggestion, query completion and search assistance, multilingual information retrieval for voice search, and ranking algorithm for revenue and music ads.

Latest Search & Recommendations Publications

April 2021 | The Web Conference

Where To Next? A Dynamic Model of User Preferences

Francesco Sanna Passino, Lucas Maystre, Dmitrii Moor, Ashton Anderson, Mounia Lalmas

March 2021 | WSDM

Shifting Consumption towards Diverse Content on Music Streaming Platforms

Christian Hansen, Rishabh Mehrotra, Casper Hansen, Brian Brost, Lucas Maystre, Mounia Lalmas

October 2020 | CIKM

Query Understanding for Surfacing Under-served Music Content

Federico Tomasi, Rishabh Mehrotra, Aasish Pappu, Judith Bütepage, Brian Brost, Hugo Galvão, Mounia Lalmas

Other Research Areas