US 12,111,839 B1
Entity matching with machine learning fuzzy logic
Elliot Hirsch, New York, NY (US); Johannes Beil, Copenhagen (DK); Lauren Brown, London (GB); Nicolas Prettejohn, Bath (GB); and Paul Baseotto, Poole (GB)
Assigned to Palantir Technologies Inc., Denver, CO (US)
Filed by Palantir Technologies Inc., Denver, CO (US)
Filed on Jun. 13, 2023, as Appl. No. 18/333,975.
Application 18/333,975 is a continuation of application No. 17/683,986, filed on Mar. 1, 2022, granted, now 11,720,580.
Claims priority of provisional application 63/156,524, filed on Mar. 4, 2021.
Int. Cl. G06F 7/00 (2006.01); G06F 16/2458 (2019.01); G06F 16/248 (2019.01)
CPC G06F 16/2468 (2019.01) [G06F 16/248 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A computerized method, performed by a computing system having one or more hardware computer processors and one or more non-transitory computer readable storage device storing software instructions executable by the computing system to perform the computerized method comprising:
identifying, for individual properties associated with a first and second set of data records, a matching algorithm selected from a plurality of matching algorithms that are configured to output a match score indicative of likelihood of a match between property values of two data records, wherein at least some of the matching algorithms are token matching, substring searches, trigram, edit-distance, metaphone, term frequency model, initialization weighting, or phrase matching;
for respective pairs of data records:
determining the matching algorithms associated with respective properties of the first and second sets of data records;
executing the plurality of matching algorithms on respective property values of the pair of data records to generate a corresponding plurality of match scores; and
determining an overall match score for the pair of data records based on at least some of the plurality of match scores; and
displaying a results user interface indicating at least a first candidate pair of data records having a highest overall match score.