Shypd.aiThe largest open index of AI toolselasticsearch-learning-to-rank is an open-source plugin that integrates machine learning with Elasticsearch to improve search relevance ranking. It allows storing features, logging relevance scores, and ranking search results using stored models.
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The elasticsearch-learning-to-rank plugin leverages machine learning to significantly enhance search relevance within Elasticsearch. It provides functionalities to store features, which are essentially Elasticsearch query templates, directly within Elasticsearch. Users can also log feature scores, which are crucial for creating training datasets for offline model development. The plugin supports storing various ranking models, including linear, XGBoost, or RankLib models, that utilize the previously stored features. Ultimately, it ranks search results based on these sophisticated models, leading to more accurate and relevant outcomes. This open-source tool is used by organizations like Wikimedia Foundation and Snagajob to power their search capabilities.
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