Which mathematical technique is MOST fundamental to retail personalization algorithms that recommend products based on past purchase history?

In today's retail environment, mathematics plays a crucial role in developing personalization algorithms that drive customer engagement and sales. From recommendation engines to dynamic pricing models, these algorithms analyze vast amounts of consumer data to create tailored shopping experiences. This trivia question tests your knowledge about the mathematical foundations that power modern retail personalization systems.

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Collaborative filtering using matrix factorization
Boolean algebra with binary decision trees
Euclidean geometry for spatial merchandising analysis
Differential calculus for continuous optimization