Learning-To-Rank
A type of machine learning algorithm used in information retrieval systems to create a model that can predict the most relevant order of a list of items, such as search engine results or product recommendations, based on features derived from the items and user queries.
Areas of application
- Information retrieval
- Search engine optimization
- Product recommendation systems
- Personalized recommendations
- Recommender systems
Example
Example: A search engine using Learning-to-Rank to rank search results based on relevance to the user query. The algorithm takes into account factors such as the content of the pages, the user’s search history, and the pages’ popularity among other users to determine the most relevant order.