Which mathematical technique is NOT commonly used in retail personalization algorithms for product recommendations?

Retail personalization algorithms have revolutionized how stores interact with customers. These sophisticated mathematical models analyze vast amounts of customer data to predict preferences and behaviors. Behind these seemingly magical recommendations are complex mathematical concepts including clustering, regression analysis, and machine learning techniques. How well do you understand the mathematical foundations that power today's retail personalization systems?

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Bayesian Probability Networks
Fourier Transform Analysis
Collaborative Filtering
K-means Clustering