Probabilistic Matching
Probabilistic matching links records to the same person by estimating likelihood from indirect signals such as device type, IP address, location, and behavior patterns. It extends reach where exact identifiers are missing, but it is less certain than deterministic matching.
Probabilistic methods assign a confidence score that several signals belong to one person. They can recover identity where no shared key exists, which matters as deterministic signals shrink.
Because it trades certainty for coverage, probabilistic matching is best used carefully, often as a fallback behind deterministic matching, and with thresholds tuned to avoid wrongly merging different people.
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