Embedding
An embedding is a numerical vector representation of text that captures its semantic meaning in a high-dimensional space. Words, sentences, or documents with similar meanings are mapped to vectors that are close together, enabling machines to measure semantic similarity mathematically. Embeddings power search, recommendations, clustering, and retrieval-augmented generation.
Example
When you search "how to fix a flat tire" in a knowledge base, the system converts your query into an embedding vector and finds articles with similar vectors — matching "changing a punctured tire" even though it uses different words, because both embeddings are close in vector space.
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