Definition
An embedding is a string of numbers that represents the meaning of a piece of text, so that things meaning similar things end up with similar numbers. It is the unit that powers semantic and vector search.
On this page
At a glance
- Categories Technical
- Related fields AI Search, Technical
- Difficulty Advanced
How Embedding Works
A model converts a word, sentence, or document into a long list of numbers, a vector, that captures its meaning. Texts about the same idea land near each other in that numeric space, even with different wording. Search systems compare embeddings to find content that means what the query means.
Why Embedding Matters
It explains why exact keywords matter less than they used to. If your content clearly conveys a concept, its embedding sits near the queries about that concept, and the system can match it without sharing a single word.
Frequently Asked Questions
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What is the difference between an embedding and a keyword?
A keyword is the literal word. An embedding captures meaning, so it can connect related ideas that use different words.
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Do I need to do anything technical with embeddings?
No. You influence them by writing clearly and on-topic. The system handles the math.