AI glossary · Building and running AI
Semantic search
Semantic search finds results based on what you mean rather than the exact words you type, using AI to understand the intent behind a query.
Also called vector search, meaning-based search, semantic similarity
In more detail
Keyword search for “cheap flights to sunny places in winter” only matches those words. Semantic search compares embeddings, so it can find a page about “budget winter getaways to the Canary Islands”.
Many search bars, help centres and AI search engines combine keyword and semantic search.
Related terms
EmbeddingAn embedding is a list of numbers that represents the meaning of a piece of text, an image or another item, so a computer can measure how similar things are.Vector databaseA vector database stores embeddings and quickly finds the ones most similar to a query, which lets AI apps search by meaning across large collections.AI search engineAn AI search engine answers your question directly in a written summary built from web pages, instead of only showing a list of links.Retrieval-augmented generation (RAG)Retrieval-augmented generation (RAG) makes AI answers more accurate by first looking up relevant information, then having the model answer using it.
Browse related tools
AI tools listed on BroUseAI in these categories.
