Entity
A distinct, uniquely identifiable thing — a person, place, organisation, product or concept — that a search engine can reason about…
Content
Semantic search
Retrieval based on the meaning of a query and documents rather than literal keyword matching, using entities, context and learned representations.
In full
The shift began with Hummingbird's query rewriting and the Knowledge Graph, deepened with neural matching, RankBrain and BERT, and now underpins both search ranking and the retrieval layer of generative answers. Practically it means synonyms, paraphrases and related concepts are understood, so exact-match keyword density is obsolete as an optimisation target. What replaces it is covering a topic in the way people actually ask about it and making entity relationships explicit.
Example
A page never containing the phrase 'how much does it cost' still ranks for it because its pricing section answers the underlying question.
Related terms
BERT
A transformer language model Google applied to search from 2019, improving understanding of word order, prepositions and context within…
Hummingbird
Google's 2013 rewrite of its core ranking infrastructure, shifting emphasis from individual keywords toward the meaning of whole queries.
Embedding
A numerical vector representing the meaning of text, an image or another item, positioned so that semantically similar items lie close…
Vector search
Retrieval by nearest-neighbour similarity between embedding vectors rather than by keyword matching, usually implemented with approximate…