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Glossary Term

Embedding.

Learn what Embedding means in modern search and SEO.

Part of speechnounOriginOld English: bedebban (to impress into) — mathematical concept formalised in machine learning research circa 2013

A numerical vector representation of text, images, or other data that captures semantic meaning in a form AI models can compute.

An embedding is a dense vector of numbers—typically hundreds or thousands of dimensions—that represents the meaning of a word, sentence, or document. Words or concepts with similar meanings end up close together in this high-dimensional space: 'king', 'queen', and 'monarch' will all cluster near each other, far from 'bicycle'.

How Embeddings Enable Semantic Search

By converting both queries and documents into embeddings, search systems can find content that matches the meaning of a query even when the exact words differ. A search for 'fixing a leaky roof' can surface articles about 'repairing roof tiles' because they occupy similar positions in embedding space.

Embeddings and SEO

Modern search engines use embeddings to evaluate topical relevance, content comprehensiveness, and entity relationships. Content that covers a topic deeply—using related concepts, entities, and questions—creates a richer embedding representation that signals expertise and depth.

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