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Web search and retrieval glossary

67 terms, defined as the field understands them. Where we do something specific, it is marked as ours rather than presented as the general case.

Verified 21 September 2026

Retrieval

15 terms

How a query becomes a set of results.

Hybrid search

Hybrid search runs a lexical query and a vector query over the same corpus and fuses the two rankings into one result set.

BM25

BM25 is a ranking function that scores documents by term frequency and inverse document frequency, with saturation so repeated terms have diminishing returns.

Semantic search

Semantic search retrieves documents by meaning rather than by word overlap, using vector embeddings to place queries and documents in a shared space.

Vector search

Vector search finds the nearest neighbours of a query vector among document vectors, usually approximately, because exact search at scale is far too slow.

Approximate nearest neighbour (ANN)

ANN search finds vectors close to a query vector without guaranteeing the exact closest, trading a small recall loss for orders-of-magnitude speed improvement.

Reciprocal rank fusion

Reciprocal rank fusion merges several ranked lists by scoring each document by the reciprocal of its position in each list, requiring no score normalisation.

Embedding

An embedding is a fixed-length vector representing the meaning of a piece of text, produced by a model so that similar texts land near each other.

Quantisation

Quantisation compresses vectors by storing each dimension in fewer bits, cutting memory and speeding comparison at a small cost in precision.

Reranking

Reranking reorders an initial candidate set with a more expensive, more accurate model than the one used to retrieve it.

Query expansion

Query expansion adds related terms to a query to improve recall when the user’s vocabulary differs from the documents’.

Recall and precision

Recall is the share of relevant documents a search returns; precision is the share of returned documents that are relevant.

Ranking

Ranking orders retrieved documents by predicted relevance, traditionally combining a text-matching score with query-independent quality signals.

Faceted search

Faceted search returns counts across categorical dimensions alongside results, letting a user or agent see the shape of a result set before reading it.

Filtering

Filtering restricts a search to documents matching structured criteria — date, language, domain, quality — before or during scoring.

Result collapsing

Collapsing groups near-identical results and returns one representative each, so a single syndicated item cannot occupy an entire result set.

Indexing

12 terms

What goes into a search index, and what it costs to keep there.

Admission control

Admission control decides at index time which documents are worth indexing at all, rather than indexing everything and sorting it out at query time.

Salient term

A salient term is a distinctive, low-frequency token identifying specific content: an error code, an identifier or a proper noun, rather than common vocabulary.

Bounded index

A bounded index caps its own size, so admitting a new document means pruning or replacing an existing one rather than simply growing.

Index pruning

Pruning removes documents from an index to reclaim space, based on redundancy, staleness, access patterns or competitive replacement.

Removal ledger

A removal ledger is an append-only record of every document removed from an index, with the reason and any replacement.

Coverage transparency

Coverage transparency is the ability to ask a search index why a specific URL is or is not present, and get a substantive answer.

Inverted index

An inverted index maps each term to the list of documents containing it, which is what makes lexical search fast.

Fast field

A fast field is a document attribute stored column-wise in the index for direct lookup, enabling filtering and sorting without reading the document.

Resident memory

Resident memory is the portion of an index that must stay in RAM to serve queries, and it is usually what caps how large an index can economically grow.

Sharding

Sharding splits an index across several nodes, each holding a portion, with a gateway scattering queries and gathering results.

Near-duplicate detection

Near-duplicate detection identifies documents with substantially the same content despite differing in wording, formatting or boilerplate.

Deduplication

Deduplication removes redundant copies of the same content from an index or a result set, so ten slots carry ten facts rather than one fact ten times.

Graphs & trust

12 terms

Relationships between documents, and judging what to believe.

Coverage graph

A coverage graph is a typed graph over a search index recording how documents relate: who published them, which report the same story, and who links to whom.

GraphRAG

GraphRAG is retrieval-augmented generation over a knowledge graph, retrieving connected subgraphs of entities rather than isolated text chunks.

Knowledge graph

A knowledge graph stores entities and the relationships between them as a queryable structure of typed nodes and edges.

Centrality

Centrality measures how well-connected a node is within a graph, and is used to identify the documents a field treats as foundational.

Host rank

Host rank scores the authority of a publishing domain from the link graph, independent of any particular query.

Corroboration

Corroboration counts how many independent sources assert the same claim, distinguishing widely reported facts from one story copied many times.

Story cluster

A story cluster groups documents reporting the same underlying event across publishers and wordings, so syndication collapses without losing the source count.

Entity extraction

Entity extraction identifies people, organisations, places and products mentioned in text and links them to canonical identifiers.

Entity dossier

A dossier is a one-hop summary of an entity: where it is mentioned, which sources cover it, and which entities appear alongside it.

Community detection

Community detection partitions a graph into clusters of nodes that reference each other far more than the rest of the graph.

Provenance

Provenance records where a document came from and how it entered the index — which crawl, when fetched, and when published.

Source lineage

Source lineage traces a reported claim back through the outlets that carried it to the origin that first published it, so that copies are not mistaken for corroboration.

Agents & context

12 terms

How autonomous systems consume retrieval.

Agentic search

Agentic search is web search consumed by an autonomous system rather than a person, which inverts most of the design assumptions of consumer search.

Retrieval-augmented generation (RAG)

RAG retrieves relevant documents and places them in a model’s context so it can answer from current, specific sources rather than from training data alone.

Context assembly

Context assembly selects, orders and truncates retrieved passages to fit a token budget before they enter a model’s context.

Context window

The context window is the maximum amount of text a model can consider at once, and it is the budget every retrieval decision spends against.

Model Context Protocol (MCP)

MCP is an open protocol for exposing tools and data sources to AI models through a uniform interface, so any compatible client can use any compatible server.

Tool use

Tool use lets a model invoke external functions — search, calculation, database queries — and incorporate the results into its reasoning.

Function calling

Function calling is a model’s ability to emit structured arguments for a named function rather than free text, enabling reliable tool invocation.

Hallucination

A hallucination is a confident, plausible model output that no source supports — including one inferred from an empty result set rather than invented outright.

Chunking

Chunking splits a document into passages small enough to embed and retrieve on their own, so a hit points at the paragraph rather than the page.

Passage

A passage is a retrievable unit of text — typically a section or several paragraphs — rather than a whole document.

Sovereign AI

Sovereign AI is the capability of a state or organisation to run AI systems on compute, models and data it controls within its own jurisdiction, without depending on foreign providers.

Evidence receipt

An evidence receipt is the structured account returned with a retrieval result of what was searched, what was not, how fresh the evidence is and which kinds of source are missing.

Crawling

7 terms

Getting the web in the first place.

Operations

9 terms

Running and paying for all of it.

From definitions to a working index

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