Ranking models in recommendation systems

Ranking models in recommendation systems are algorithms designed to order items—like products, movies, or songs—based on how likely a user is to engage with them. They analyze user preferences, behaviors, and item attributes to predict relevance, then generate a prioritized list. This helps users find the most suitable options quickly, enhancing their experience. Essentially, ranking models weigh various factors to present the best options at the top, ensuring that recommendations are both personalized and useful.