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

Retail personalization algorithms rely heavily on mathematical concepts to deliver tailored shopping experiences. These algorithms analyze customer behavior patterns, purchase history, and preferences to create individualized recommendations. Behind the scenes, complex mathematical frameworks power these systems. How well do you understand the mathematical foundations that drive modern retail personalization technology?

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Matrix Factorization
Laplace Transforms
Polynomial Regression
Fourier Analysis