Definition

Embedding

An embedding is a high-dimensional vector representation of text, used to retrieve semantically similar content rather than keyword-matched content.

Embeddings are why synonyms and paraphrases retrieve the same source, and why exact-match keyword density has little bearing on AI citation.

They also mean unclear writing is penalised twice: once by readers and once by retrieval that cannot place the passage.

Related terms

Chunk Retrieval-augmented generation (RAG)Semantic search

Nostimates measures embedding across twelve AI answer surfaces. Request access →

All terms

AEO (Answer Engine Optimisation)GEO (Generative Engine Optimisation)AI Overviews AI Mode Citation share n-sampling Query fan-out Grounding Share of voice (AI)Extraction success rate Surface Answer engine Citation Brand mention Mention rate Confidence interval Statistical significance Citation volatility Non-determinism Reproducibility Identity-free collection Personalisation Locale Residential proxy Bot detection Collection cost Credit Evidence retention Audit trail Parser version Canary prompt Data freshness Cadence Prompt set Head term Long-tail query Competitive set llms.txt robots.txt AI crawler Training crawler Retrieval-augmented generation (RAG)Hallucination Answer box Featured snippet Zero-click search Entity Entity salience Knowledge graph Structured data JSON-LD schema.org FAQ schema Answer-first content Chunk Semantic search Prompt injection Market coverage Sentiment analysis Position tracking White-label data