AI SEO Glossary
What is Semantic Search?
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TL;DR — Semantic search is retrieval that matches a query's meaning and intent rather than its literal words, using embeddings and language models to understand that different phrasings ask the same thing. It is how modern engines — Google since BERT and MUM, and every LLM-based answer engine — select candidate content: pages are retrieved because they answer the intent, even when they never use the query's exact wording. For optimizers, semantic search retired keyword-variant page sprawl; one authoritative page can satisfy an entire family of phrasings, and thin variant pages just compete with themselves.
Definition & scope
The practical shift is from keywords to questions and entities: cover the intent completely, use the vocabulary buyers actually use naturally, and let one strong page own the meaning-space rather than splitting it across near-duplicates.
Semantic retrieval is also the front half of every AI answer: engines retrieve semantically, then cite from what they retrieved — so semantic relevance is the qualifying round for AI citations.
Related terms
- Vector Embeddings — the representation semantic search runs on.
- Query Fan-Out — how AI engines expand intent into sub-queries.
- Entity SEO — entities anchor meaning-based matching.
Related services
- AI SEO Services — intent-complete content built for semantic retrieval.