Which mathematical algorithm is MOST commonly used as the foundation for retail product recommendation engines?

Retail personalization has become increasingly sophisticated, leveraging advanced mathematical algorithms to predict customer preferences and behavior. These systems analyze purchase history, browsing patterns, and demographic data to create tailored shopping experiences. But do you know which mathematical concepts power these personalized recommendations that drive sales and customer retention?

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Collaborative Filtering using matrix factorization
Bayesian Networks with decision trees
Markov Chain Monte Carlo simulations
Convolutional Neural Networks with tensor analysis