Personalization, Algorithms, Recommendation System.
satisfaction that users derive from interacting with the recommended items. It combines factors like relevance, diversity, and novelty. A/B Testing and Offline Evaluation: A/B testing involves conducting controlled experiments where different recommendation algorithms are compared in real-world