Glossary term
Embedding
A numerical vector representing the meaning of text, images or other data, so that similar items have nearby vectors.
Embedding models convert passages and queries into vectors. Similarity between vectors is used for semantic search, clustering and deduplication.
Embeddings capture meaning well but can miss exact identifiers such as product codes, which is why they are often combined with keyword search.
Related terms
- Vector databaseA data store optimised for finding the vectors most similar to a query vector, used for semantic search over embeddings.
- Hybrid searchCombining keyword-based and vector-based retrieval, then merging and re-ranking the results.
- Retrieval-augmented generation (RAG)A pattern in which relevant passages are retrieved from a body of content and given to a language model to ground its answer.
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