Which pioneering algorithm, developed in the late 1990s, revolutionized product recommendations by analyzing user-item interactions through matrix factorization and became foundational for modern retail recommendation systems?

Recommendation systems have revolutionized how consumers discover products, evolving from simple statistical methods to sophisticated AI-driven technologies. These algorithms analyze consumer behavior, purchase history, and preferences to suggest relevant products, significantly increasing conversion rates and customer satisfaction. This trivia question focuses on a key innovation that transformed recommendation engines in the retail industry.

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Collaborative Filtering
Random Forest Recommender
Neural Network Preference Model
Bayesian Preference Algorithm