Accelerating Creator Audience Building through Centralized Exploration

Buket Baran,Guilherme Dinis Junior, Antonina Danylenko, Olayinka S. Folorunso, Gosta Forsum,Maksym Lefarov,Lucas Maystre, Yu Zhao

PROCEEDINGS OF THE 17TH ACM CONFERENCE ON RECOMMENDER SYSTEMS, RECSYS 2023(2023)

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摘要
On Spotify, multiple recommender systems enable personalized user experiences across a wide range of product features. These systems are owned by different teams and serve different goals, but all of these systems need to explore and learn about new content as it appears on the platform. In this work, we describe ongoing efforts at Spotify to develop an efficient solution to this problem, by centralizing content exploration and providing signals to existing, decentralized recommendation systems (a.k.a. exploitation systems). We take a creator-centric perspective, and argue that this approach can dramatically reduce the time it takes for new content to reach its full potential.
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