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 2023 | ACM TORS

Unbiased Identification of Broadly Appealing Content Using a Pure Exploration Infinitely-Armed Bandit Strategy

Maryam Aziz, Jesse Anderton, Kevin Jamieson, Alice Wang, Hugues Bouchard, Javed Aslam

October 2023 | CIKM

Exploiting Sequential Music Preferences via Optimisation-Based Sequencing

Dmitrii Moor, Yi Yuan, Rishabh Mehrotra, Zhenwen Dai, Mounia Lalmas

October 2023 | CIKM

Graph Learning for Exploratory Query Suggestions in an Instant Search System

Enrico Palumbo, Andreas Damianou, Alice Wang, Alva Liu, Ghazal Fazelnia, Francesco Fabbri, Rui Ferreira, Fabrizio Silvestri, Hugues Bouchard, Claudia Hauff, Mounia Lalmas, Ben Carterette, Praveen Chandar, David Nyhan

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