2024/10/08 by Henrik Lindström, Humberto Jesús Corona Pampín, Enrico Palumbo +1 · 1 voice · 1 citation
Computer Science · #Caching and Content Delivery #Information Retrieval and Search Behavior #Recommender Systems and Techniques
paper · pdf · doi:10.1145/3640457.3688035
openalex publication_date 2024/10/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/30
At Spotify, search has been traditionally seen as a tool for retrieving content, with the search system optimized for when the user has a specific target in mind. In particular we have relied on an instant search system providing results for each keystroke, which works well for known-item search, when queries are straightforward, and the catalog is small. However, as Spotify’s catalog grows in size and variety, it becomes increasingly difficult for users to define their search intents accurately. Furthermore, as we expand the offering, we need to help users discover more content both when it comes to new content types, e.g. audiobooks, as well as for new content/creators within existing content types. To solve this we have introduced a hybrid Query Recommendation system (QR) that helps the user formulate more complex exploratory search intents, while still serving known-item lookups efficiently. This experience has been rolled out worldwide to all mobile users resulting in an increase in exploratory intent queries of 9% in A/B tests.