Which mathematical algorithm is MOST commonly used as the foundation for collaborative filtering in retail product recommendation systems?

In today's data-driven retail environment, machine learning algorithms play a crucial role in personalized product recommendations. These systems rely on complex mathematical models to analyze customer behavior and predict preferences. This poll tests your knowledge of the mathematical foundations behind retail recommendation engines that power the shopping experience across major platforms.

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Singular Value Decomposition (SVD)
Convolutional Neural Networks (CNN)
Fourier Transform Analysis
Markov Decision Processes