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Summary:
Recommendation Engines are essential for the success of online platforms, as they use algorithms to predict user preferences and make personalized recommendations. These engines lead to increased customer engagement, better experiences, and higher revenue for the platform. User-based collaborative filtering is a popular technique that uses user-item interaction data to identify similarities between users and make accurate predictions.