Which mathematical technique forms the foundation of most basic retail recommendation systems by identifying patterns between products frequently purchased together?

Personalization algorithms have revolutionized how we shop online, using sophisticated mathematical models to predict consumer behavior. These systems analyze our browsing patterns, purchase history, and demographic information to create tailored shopping experiences. Behind these seemingly magical recommendations lies complex mathematics - from collaborative filtering to deep neural networks. Test your knowledge about the mathematical foundations that power modern retail personalization systems!

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Association rule learning (market basket analysis)
Gaussian mixture modeling
Principal component analysis (PCA)
Bayesian hierarchical clustering