Learning to Rank

Learning to Rank is a method used by search engines and recommendation systems to improve the order of results based on how relevant they are to the user’s query. It involves training algorithms to analyze various features of items—like keywords, popularity, or user behavior—and then rank them so the most useful or relevant items appear higher. This process uses example data to learn patterns and make smarter ranking decisions over time, enhancing the user experience by delivering more accurate and personalized search or recommendation results.