By the Variask team · Updated
Definition
Hybrid search combines keyword search with vector search, so results match both the exact words in a query and its meaning. Many AI retrieval systems use it.
Keyword search is precise for names, model numbers and exact phrases. Vector search is better with paraphrases and intent. Combining them, then reranking the results, gives AI assistants passages that are both relevant and exact.
Questions
Not much beyond good writing: clear names and specifics for keyword matching, and natural explanations for meaning based matching.
Related terms
How AI search works
Vector search
Vector search finds content by meaning instead of exact words. Text is turned into lists of numbers called embeddings, and the search returns the items whose numbers sit closest to the question's.
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Semantic search
Semantic search is search that understands the meaning and intent behind a query, not only its exact words, so it can return results that answer the question even when they use different wording.
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Embeddings
An embedding is a list of numbers that captures the meaning of a piece of text, so that texts with similar meaning get similar numbers. AI systems use embeddings to find, group and compare content.
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Retrieval-augmented generation (RAG)
Retrieval-augmented generation (RAG) is a way of building AI answers where the system first retrieves relevant documents or web pages, then has the language model write the answer using them.
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