Which mathematical algorithm is MOST commonly used as the foundation for retail product recommendation systems that suggest 'customers who bought X also bought Y'?

Retail personalization algorithms leverage mathematical models to predict consumer behavior and optimize shopping experiences. Behind these powerful recommendation systems are sophisticated mathematical concepts that transform raw data into actionable insights. Test your knowledge of how mathematics powers modern retail personalization technology!

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Collaborative Filtering using matrix factorization
Dijkstra's Shortest Path Algorithm
Monte Carlo Simulation
Eigenvalue Decomposition of customer preference vectors