Which machine learning technique is MOST commonly used as the foundation for music recommendation systems on major streaming platforms?

Streaming platforms have transformed how we discover and consume music, with personalized recommendations playing a crucial role in user engagement. Behind these seemingly magical suggestions lies sophisticated machine learning. This poll tests your knowledge of how these recommendation systems work and their impact on the music industry ecosystem, from artists to listeners.

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Collaborative Filtering, which recommends music based on similar listening patterns among users
Supervised Classification, which categorizes songs into predefined genres based on training data
Natural Language Processing, which analyzes lyrics to match songs with similar themes
Reinforcement Learning, which optimizes recommendations based on whether users skip or complete songs