Category: AI Search & Discovery
Definition:
Semantic Search is a search approach that focuses on understanding the meaning, context, intent, and relationships behind a user’s query rather than relying only on exact keyword matches.
Why it matters:
People rarely search using perfectly precise keywords. They use natural language, variations, questions, and conversational phrases.
Semantic Search helps AI and search systems understand what a user actually means and connect that intent with relevant information—even when the wording on a webpage is different from the wording in the query.
Example:
A user searches for “how to make my website appear in ChatGPT recommendations.” A semantic search system can understand that the user is looking for information about AI visibility, GEO, citations, and AI search optimisation, even if those exact terms aren’t used in the query.
Semantic Search vs. Keyword Search:
Keyword Search primarily matches words or phrases.
Semantic Search considers meaning, context, intent, and relationships between concepts.
Related terms:
AI Search · Search Intent · Natural Language Processing (NLP) · Knowledge Graph · Entity · Generative Search · Retrieval-Augmented Generation (RAG)
In simple terms:
Semantic Search is search that tries to understand what you mean, not just the words you typed.
