A model typically embeds the query and indexed items into a shared vector space. Nearest items become candidates, which may then be filtered or reranked with additional signals.
Semantic search retrieves information by the meaning of a query rather than relying only on exact word overlap.
A model typically embeds the query and indexed items into a shared vector space. Nearest items become candidates, which may then be filtered or reranked with additional signals.