Which mathematical technique is MOST commonly used in retail personalization algorithms to predict products a customer might want to purchase based on their browsing history?

Retail personalization algorithms are revolutionizing how mathematics is applied in the consumer world. These sophisticated mathematical models analyze customer behavior, preferences, and purchase history to create tailored shopping experiences. Behind these systems are complex mathematical concepts that many shoppers never see but experience daily. Test your knowledge about how mathematics powers retail personalization and shapes the future of shopping.

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Collaborative filtering using matrix factorization
Differential calculus with partial derivatives
Euclidean geometry with spatial mapping
Fourier transform analysis of purchase frequency