Which mathematical technique revolutionized retail personalization algorithms by enabling systems to identify hidden patterns in customer preference data without being explicitly programmed?

In today's retail landscape, mathematical algorithms drive personalized shopping experiences like never before. Advanced computational models now process vast amounts of customer data to deliver tailored recommendations, predict purchasing behavior, and optimize inventory. How well do you understand the mathematics behind modern retail personalization technology?

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Collaborative filtering with singular value decomposition (SVD)
Bayesian probability networks with Markov chains
Euclidean distance clustering with k-means
Monte Carlo simulations with reinforcement learning