Semantic search
Retrieval based on the meaning of a query and documents rather than literal keyword matching, using entities, context and learned…
ContentTerm frequency-inverse document frequency
TF-IDF
A classical information-retrieval weighting that scores a term by how often it appears in a document offset by how common it is across the corpus.
In full
TF-IDF and its refinement BM25 remain the backbone of lexical retrieval and are still used in hybrid systems alongside vector search. In SEO the term is mostly encountered through content-optimisation tools that compare a draft's term distribution against ranking pages. Treated as a diagnostic for missing subtopics it is useful; treated as a target to hit a term count it recreates keyword stuffing with extra steps.
Example
A tool flags that top-ranking pages for a query all discuss 'security deposit' and 'notice period', terms the draft omits entirely.
Related terms
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…
Keyword research
Identifying and prioritising the queries a business should target, using volume, difficulty, intent, business value and current visibility.
Content brief
A specification given to a writer covering the target query set, intent, required subtopics, angle, sources, internal links and success…