Glossary

Plain definitions for the terms used in identity resolution, audiences and agentic data work.

Identity resolution
Deciding whether different records describe the same real person, household or business, then linking them under one identity.
Entity resolution
The general form of identity resolution, applied to any kind of entity: people, businesses, products or places.
Record linkage
The technical task of finding records that refer to the same entity across or within datasets.
Deterministic matching
Linking records when specific fields match exactly or near exactly, such as an email or a phone number.
Probabilistic matching
Estimating the likelihood that two records match from the agreement of many fields. The Fellegi-Sunter model is the classic method.
Semantic matching
Comparing what records mean rather than how their text reads, using vector embeddings, so variants like Jo Jo and Johnny can converge.
Contextual record linkage
DarkMath’s term for linking records using context such as contact history, moves, vehicles and behavior, in addition to identifiers.
Vector embedding
A list of numbers that describes the meaning of a record. Records with similar meaning have embeddings that sit close together.
Semantic Gravity
DarkMath’s name for the way related signals cluster around one identity in vector space, pulling new data toward the profile it fits best.
Golden Record
The single, auditable profile for one resolved identity, with the sources and reasons behind every merge.
Household
People who share a residence and often share purchase decisions, built from resolved individuals.
Persistent ID
An identifier that stays stable for a person or household as their records change over time.
Match rate
The share of records linked to at least one other record. It can rise from bad guesses, so read it with precision.
Precision
Of the links a system made, the share that are correct.
Recall
Of the true links in the data, the share the system found.
F1 score
The harmonic mean of precision and recall. One number that rewards finding links without making false ones.
False merge
Two different people combined into one identity, such as a father and son at the same address.
Cognitive Data Graph
DarkMath’s connected model of resolved people, households, attributes, events and outcomes, each with its source, time, confidence and permitted use.
Semantic attribute
An inferred characteristic, such as life stage or media habits, derived from patterns in other data rather than read from one field.
Seed audience
The list of existing customers a lookalike model learns from.
Semantic lookalike
A person or household whose behavior and context resemble a seed audience in vector space.
Synthetic data
Realistic records generated for testing, demonstrations or training, clearly labeled and kept separate from real people.
The Corruptor
DarkMath’s controlled perturbation engine. It adds realistic errors to copies of records with known identities so matching methods can be scored against the truth.
Clean room
A secure environment where two parties analyze combined data without either seeing the other’s raw records.
Anonymous ID
A key that links records without carrying personal information, used to connect data between parties.
Re-identification gate
The control point where an anonymous result can be tied back to a person, allowed only with the data owner’s authorization.
Contact coverage
For a given audience, the share of records reachable by each channel, such as postal address, email or mobile ad ID.
Hashed email
An email address converted into a fixed code by a one-way function, used to match records without exchanging the address itself.
Agentic workflow
A sequence where software plans steps, uses tools and prepares actions toward a goal, with people approving what runs.

See the terms in action.

The DarkMatch demo shows a missed link and a false merge on five ordinary records.