pEBR: A Novel Probabilistic Embedding based Retrieval Model to Address the Challenges of Insufficient Retrieval for Head Queries and Irrelevant Retrieval for Tail Queries

" data-medium-file="https://www.marktechpost.com/wp-content/uploads/2024/11/Screenshot-2024-11-03-at-10.41.09 PM-300x178.png" data-large-file="https://www.marktechpost.com/wp-content/uploads/2024/11/Screenshot-2024-11-03-at-10.41.09 PM-1024x606.png" tabindex="0" role="button"> " data-medium-file="https://www.marktechpost.com/wp-content/uploads/2024/11/Screenshot-2024-11-03-at-10.41.09 PM-300x178.png" data-large-file="https://www.marktechpost.com/wp-content/uploads/2024/11/Screenshot-2024-11-03-at-10.41.09 PM-1024x606.png" tabindex="0" role="button">Creating a common semantic space where queries and items can be represented as dense vectors is the main goal of embedding-based retrieval. Instead of depending on precise keyword matches, this method enables effective matching based on semantic similarities. Semantically related things are positioned closer to one another in this common area since searches and items […]

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