US 12,461,972 B2
System and method for genealogical entity resolution
Tyler Folkman, Lehi, UT (US); Rey Furner, Lehi, UT (US); and Drew Pearson, Lehi, UT (US)
Assigned to Ancestry.com Operations Inc., Lehi, UT (US)
Filed by Ancestry.com Operations Inc., Lehi, UT (US)
Filed on Mar. 13, 2024, as Appl. No. 18/603,537.
Application 18/603,537 is a continuation of application No. 17/261,458, granted, now 11,960,548, previously published as PCT/US2019/042807, filed on Jul. 22, 2019.
Claims priority of provisional application 62/701,322, filed on Jul. 20, 2018.
Prior Publication US 2024/0220547 A1, Jul. 4, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 16/00 (2019.01); G06F 16/215 (2019.01); G06F 16/22 (2019.01); G06F 16/25 (2019.01); G06F 16/28 (2019.01); G06F 16/906 (2019.01); G06F 18/22 (2023.01); G06N 3/045 (2023.01); G06N 20/20 (2019.01)
CPC G06F 16/906 (2019.01) [G06F 16/215 (2019.01); G06F 16/2246 (2019.01); G06F 16/258 (2019.01); G06F 16/287 (2019.01); G06F 18/22 (2023.01); G06N 3/045 (2023.01); G06N 20/20 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
extracting, from a first tree node of a first data tree comprising a first plurality of interconnected nodes representing relationships among a first set of tree persons, a first set of features using a feature extractor;
extracting, from a second tree node of a second data tree comprising a second plurality of interconnected nodes representing relationships among a second set of tree persons, a second set of features using the feature extractor;
identifying, within a cluster database storing clusters of tree nodes and from the first set of features and the second set of features, a cluster comprising a set of tree nodes including tree nodes from the first data tree and the second data tree, wherein the set of tree nodes corresponds to a single tree person by:
generating an individual-level similarity score between the first tree node and the second tree node;
generating additional individual-level similarity scores between additional nodes of the first plurality of interconnected nodes within the first data tree and additional nodes of the second plurality of interconnected nodes within the first data tree and additional nodes of the second plurality of interconnected nodes within the second data tree; and
determining the cluster based on the individual-level similarity score and the additional individual-level similarity scores; and
based on identifying the cluster comprising the set of tree nodes corresponding to the single tree person, modifying the cluster database to include the cluster representing the single tree person.