Letor

Letor, short for "Learning to Rank," is a technique used in information retrieval systems, like search engines, to improve the relevance of search results. It involves training algorithms to understand which results best match user queries by analyzing features such as relevance scores, click patterns, and document quality. The goal is to prioritize the most useful and accurate results at the top of the list, making searches more efficient and satisfying for users. Essentially, Letor helps computers learn how to better rank information based on what users find most helpful.