Cross-list learning to rank
Topics: Learning-to-rank, Ranking, Scoring, Search Query Processing, User Signals
The Google patent describes a method for enhancing machine learning models used in ranking items by employing a technique known as “cross-list learning to rank.” This method utilizes training data derived from multiple queries and their corresponding responsive items to improve the efficiency and effectiveness of ranking models. By processing pairs of items from different training examples and evaluating their relationships, the method aims to generate a more accurate ranking based on their correlation, leading to better recommendations in applications like search engines and recommendation systems.
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