One of the main innovations rediscovered in the last years in search and machine learning is the concept of Embeddings. In search, embeddings have been used in many different applications including retrieval, advertising, and recommender systems. In this talk we are going to show some applications of vector space embeddings that have considerably improved the state of the art. All the applications shown have been adopted by main search companies in production in their systems.


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