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

November 2024 | SIAM Journal on Mathematics of Data Science

Topological Fingerprints for Audio Identification

Wojciech Reise, Ximena Fernández, Maria Dominguez, Heather A. Harrington, Mariano Beguerisse-Díaz

June 2024 | ICWSM

Socially-Motivated Music Recommendation

Ben Lacker, Samuel Way

May 2024 | Yijun Tian, Maryam Aziz, Alice Wang, Enrico Palumbo and Hugues Bouchard

Structural Podcast Content Modeling with Generalizability

Yijun Tian, Maryam Aziz, Alice Wang, Enrico Palumbo and Hugues Bouchard

Other Research Areas