Which mathematical concept is NOT typically used in retail personalization algorithms that generate product recommendations?

In today's data-driven retail environment, personalization algorithms are transforming how businesses connect with customers. These sophisticated systems rely on complex mathematical principles to analyze shopping patterns, predict preferences, and deliver tailored experiences. How well do you understand the mathematical foundations that power these retail recommendation engines? Test your knowledge of the algorithms that drive personalized shopping experiences in the digital age.

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Markov Chains for modeling sequential purchase patterns
Gödel's Incompleteness Theorems for identifying product relationships
Collaborative filtering using cosine similarity metrics
Bayesian inference for predicting customer preferences