IP Library › Patent Application 19309255
Patent Application
App. No. 19/309,255

DETERMINING AND CLUSTERING MATCHES OF MATCHES USING CUSTOM ALGORITHMS

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Quick Facts
Patent No.
US None
App. No.
19/309,255
Abstract

The present disclosure is directed toward systems, methods, and non-transitory computer-readable media for generating a matched-data-link tree defining relationships among individuals according to genetic data. For example, the disclosed systems can determine matches of matches using a novel matching database structure. The disclosed systems encode integers based on data matches of a data identifier and populate a match database with the integers. Correlating data match integers for a data identifier with data match integers for data matches, the disclosed systems generate matches of matches. The disclosed systems can generate relationship clusters from matches of matches. For example, the disclosed systems compare sets of data matches to discover groups of data matches with stronger data-match levels.

Claims (45)

1 . A computer-implemented method comprising:

determining, for a data identifier, a set of data matches across a plurality of data-match levels;

updating a match database to include the set of data matches for the data identifier by adding a set of integers encoding the set of data matches, wherein the match database comprises a table of rows representing data identifiers such that a row in the table includes integers defining data matches for a respective data identifier; and

generating a matches-of-matches prediction for the data identifier by querying the match database for integers in rows corresponding to the set of data matches of the data identifier.

2 . The computer-implemented method of claim 1 , wherein generating the matches-of-matches prediction comprises determining, for the data identifier, a matches-of-matches set comprising data matches of data matches corresponding to the data identifier.

3 . The computer-implemented method of claim 2 , further comprising generating, utilizing one or more relationship prediction models to process the matches-of-matches set, relationship predictions indicating types of data links among the matches-of-matches set.

4 . The computer-implemented method of claim 3 , further comprising generating, for the data identifier, a relationship cluster from the relationship predictions using a relationship clustering algorithm.

5 . The computer-implemented method of claim 4 , wherein generating the relationship cluster from the relationship predictions using the relationship clustering algorithm further comprises:

examining, for a candidate relationship cluster, edges between data identifiers in the relationship cluster;

calculating connectivity values for the data identifiers based on examining the edges; and

removing at least one data identifier from the candidate relationship cluster according to the connectivity values.

6 . The computer-implemented method of claim 5 , wherein calculating the connectivity values for the data identifiers further comprises:

determining, by comparing a first data identifier with the other data identifiers in the candidate relationship cluster, a quantity of matches that the first data identifier has with the other data identifiers in the candidate relationship cluster; and

calculating a connectivity value for the first data identifier by comparing the quantity of matches for the first data identifier with the total number of the other data identifiers in the candidate relationship cluster.

7 . The computer-implemented method of claim 5 , further comprising generating, by removing the at least one data identifier from the relationship cluster, the relationship cluster as a filtered relationship cluster.

8 . A non-transitory computer readable medium storing instructions which, when executed by at least one processor, cause the at least one processor to:

determine, for a data identifier, a set of data matches across a plurality of data-match levels;

update a match database to include the set of data matches for the data identifier by adding a set of integers encoding the set of data matches, wherein the match database comprises a table of rows representing data identifiers such that a row in the table includes integers defining data matches for a respective data identifier; and

generate a matches-of-matches prediction for the data identifier by querying the match database for integers in rows corresponding to the set of data matches of the data identifier.

9 . The non-transitory computer readable medium of claim 8 , further comprising instructions which, when executed by the at least one processor, cause the at least one processor to determine data matches from the set of data matches that exceed a threshold data-match level.

10 . The non-transitory computer readable medium of claim 9 , further comprising instructions which, when executed by the at least one processor, cause the at least one processor to:

separate a first subset of data matches from the set of data matches into a first category corresponding to a first data-match level;

separate a second subset of data matches from the set of data matches into a second category corresponding to a second data-match level; and

remove the data matches from the set of data matches that exceed the threshold data-match level.

11 . The non-transitory computer readable medium of claim 10 , further comprising instructions which, when executed by the at least one processor, cause the at least one processor to determine the matches-of-matches set by intersecting the first subset of data matches in the first category with the second subset of data matches in the second category.

12 . The non-transitory computer readable medium of claim 11 , further comprising instructions which, when executed by the at least one processor, cause the at least one processor to generate match clusters for the matches-of-matches set utilizing a set of clustering methods comprising Louvain community detection, spectral clustering, and agglomerative hierarchical clustering.

13 . The non-transitory computer readable medium of claim 12 , further comprising instructions which, when executed by the at least one processor, cause the at least one processor to filter the match clusters for the matches-of-matches set by connectivity value and threshold data-match level.

14 . The non-transitory computer readable medium of claim 13 , further comprising instructions which, when executed by the at least one processor, cause the at least one processor to refine the match clusters for the matches-of-matches set by repeating, for multiple iterations:

clustering the match clusters for the matches-of-matches set using the set of clustering methods; and

filtering the match clusters for the matches-of-matches set by connectivity and threshold data-match level, wherein the connectivity and threshold data-match level vary for each iteration.

15 . A system comprising:

one or more memory devices; and

one or more processors coupled to the one or more memory devices, wherein the one or more processors are configured to cause the system to:

determine, for a data identifier, a set of data matches across a plurality of data-match levels;

update a match database to include the set of data matches for the data identifier by adding a set of integers encoding the set of data matches, wherein the match database comprises a table of rows representing data identifiers such that a row in the table includes integers defining data matches for a respective data identifier; and

generate a matches-of-matches prediction for the data identifier by querying the match database for integers in rows corresponding to the set of data matches of the data identifier.

16 . The system of claim 15 , wherein the one or more processors are further configured to provide the matches-of-matches prediction to a match calculator.

17 . The system of claim 16 , wherein the one or more processors are further configured to:

generate, by the match calculator, additional match data for the matches-of-matches prediction; and

utilize the additional match data to generate a relationship cluster.

18 . The system of claim 15 , wherein the one or more processors are further configured to:

store the integers by converting the integers into an array of bytes; and

upon receiving a request for an integer from the integers, convert the array of bytes back into the integer.

19 . The system of claim 15 , wherein the one or more processors are further configured to generate, for display within a graphical user interface of a client device, a relationship cluster diagram.

20 . The system of claim 15 , wherein the one or more processors are further configured to remove one or more data matches from the set of data matches according to a data link type associated with the data identifier.

Assignments (5)
PATENT SECURITY AGREEMENT Recorded Aug 3, 2026
From: ANCESTRY.COM OPERATIONS INC.; ANCESTRY.COM DNA, LLC
To: WILMINGTON TRUST, NATIONAL ASSOCIATION, AS NOTES COLLATERAL AGENT
Reel/Frame 076116/0447 →
PATENT SECURITY AGREEMENT Recorded Aug 3, 2026
From: ANCESTRY.COM OPERATIONS INC.; ANCESTRY.COM DNA, LLC
To: WILMINGTON TRUST, NATIONAL ASSOCIATION, AS NOTES COLLATERAL AGENT
Reel/Frame 076144/0726 →
CORRECTIVE ASSIGNMENT TO CORRECT THE ASSIGNEE AS FILED, ANCESTRY.COM DNA, LLC, IS INCORRECT AND SHOULD BE CORRECTED TO ANCESTRY.COM OPERATIONS INC. AS LISTED ON THE EXECUTED ASSIGNMENT. PREVIOUSLY RECORDED ON REEL 72113 FRAME 324. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Aug 29, 2025
From: CURTIS, ROSS EUGENE; CURTIS, DONALD BERNARD; PAVLOVIC, MILOS; GREENWOOD, EUGENE DAVID; LIU, CHAOZHONG
To: ANCESTRY.COM OPERATIONS INC.
Reel/Frame 072761/0622 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 25, 2025
From: CURTIS, ROSS EUGENE; CURTIS, DONALD BERNARD; PAVLOVIC, MILOS; GREENWOOD, EUGENE DAVID; LIU, CHAOZHONG
To: ANCESTRY.COM DNA, LLC
Reel/Frame 072113/0324 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 25, 2025
From: ANCESTRY.COM OPERATIONS INC.
To: ANCESTRY.COM DNA, LLC
Reel/Frame 072113/0420 →