Dense Retrieval
A retrieval technique that uses dense vector embeddings to identify semantically relevant documents based on similarity in an embedding space.
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Related terms
A machine learning model that converts text, images, audio, or other data into dense numerical vector representations that capture semantic meaning for retrieval, similarity search, and related AI tasks.
Semantic SearchA search technique that analyzes sentence meaning and intent rather than matching literal keywords.
Hybrid SearchA retrieval technique that combines semantic vector search with keyword-based lexical search to improve the relevance, accuracy, and recall of retrieved information by leveraging the strengths of both approaches.
RetrieverA system component responsible for fetching relevant documents or passages from a knowledge base given a query.
Sparse RetrievalA search technique that uses term frequency and keyword matching, such as BM25, to locate relevant documents within a corpus.