Which recommendation algorithm technique revolutionized music streaming platforms by significantly reducing churn rates through its ability to discover long-tail content for users?

The music industry has been transformed by recommendation systems that help listeners discover new artists and songs. These sophisticated algorithms analyze listening patterns, preferences, and behaviors to create personalized experiences. Behind the scenes, music streaming platforms employ various techniques to keep users engaged and reduce churn. Test your knowledge about how these systems work and their impact on the modern music landscape.

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Collaborative filtering that identifies similar users and recommends music they've enjoyed
Matrix factorization that identifies latent features connecting users to undiscovered artists
Content-based filtering that analyzes audio features like tempo, key, and instrumentation
Reinforcement learning that optimizes for immediate user engagement metrics