A search method based on semantic similarity rather than keyword matching. Instead of looking for exact words, vector search converts content and queries into mathematical vectors (embeddings) and finds the most semantically similar results. This allows search to understand meaning — so “tall building” and “skyscraper” are recognized as similar even though they share no keywords. AI systems and modern retrieval methods use vector search heavily, which means keyword-stuffed content is less valuable than semantically coherent, well-organized content. For SEO in the AI era, this means writing for clarity and topical cohesion rather than optimizing for keyword density.
Part of the Plain Intelligence glossary. See all terms.