Which mathematical technique is MOST commonly used as the foundation for retail personalization algorithms that recommend products based on previous purchase history?

In today's data-driven retail environment, mathematical algorithms form the backbone of personalization systems that enhance customer experience. These sophisticated mathematical models analyze customer behavior patterns and preferences to deliver tailored recommendations and experiences. How well do you understand the mathematical foundations behind these powerful retail personalization tools?

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Differential calculus
Collaborative filtering using matrix factorization
Trigonometric transformations
Euclidean geometry