learning to rank
**learning to rank**
What is learning to rank?
Learning to rank (LTR) is a type of supervised machine learning where the goal is to train a model that can sort a list of items in a way that optimizes some relevance or utility metric. It's commonly used in information retrieval systems like search engines and recommendation systems. Instead of predicting a discrete category or continuous value, LTR models predict a ranking or ordering of items based on their relevance to a given query or context. Features of both the query and the item (e.g., keywords, item popularity, user history) are used as input to the model. The output is a ranking score that determines the item's position in the ordered list.
What other technologies are related to learning to rank?
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