US 12,298,969 B2
Apparatus, systems, and methods for grouping data records
Boris Shimanovsky, Los Angeles, CA (US); Manuel Lagang, Pasadena, CA (US); and Leonid Polovets, Menlo Park, CA (US)
Assigned to FOURSQUARE LABS, INC., New York, NY (US)
Filed by FOURSQUARE LABS, INC., New York, NY (US)
Filed on Nov. 9, 2020, as Appl. No. 17/093,151.
Application 17/093,151 is a continuation of application No. 14/214,231, filed on Mar. 14, 2014, granted, now 10,831,725.
Claims priority of provisional application 61/800,036, filed on Mar. 15, 2013.
Claims priority of provisional application 61/799,846, filed on Mar. 15, 2013.
Claims priority of provisional application 61/799,131, filed on Mar. 15, 2013.
Claims priority of provisional application 61/799,986, filed on Mar. 15, 2013.
Claims priority of provisional application 61/799,817, filed on Mar. 15, 2013.
Prior Publication US 2021/0303531 A1, Sep. 30, 2021
Int. Cl. G06N 20/00 (2019.01); G05B 13/02 (2006.01); G06F 16/21 (2019.01); G06F 16/23 (2019.01); G06F 16/2455 (2019.01); G06F 16/2458 (2019.01); G06F 16/28 (2019.01); G06F 16/29 (2019.01); G06F 16/31 (2019.01); G06F 16/35 (2019.01); G06F 16/951 (2019.01); G06N 5/022 (2023.01); G06Q 10/101 (2023.01); G06Q 30/0251 (2023.01); G06Q 30/0282 (2023.01); G06Q 50/00 (2024.01); H04L 41/14 (2022.01); H04W 4/02 (2018.01); H04W 4/021 (2018.01); H04W 4/029 (2018.01); H04W 4/50 (2018.01); H04W 8/08 (2009.01); H04W 8/16 (2009.01); H04W 8/18 (2009.01); H04W 16/24 (2009.01); H04W 64/00 (2009.01); H04W 76/38 (2018.01); H04W 88/02 (2009.01); G06F 16/335 (2019.01); H04W 16/00 (2009.01); H04W 16/30 (2009.01); H04W 16/32 (2009.01); H04W 88/00 (2009.01)
CPC G06F 16/21 (2019.01) [G05B 13/0265 (2013.01); G06F 16/23 (2019.01); G06F 16/235 (2019.01); G06F 16/2379 (2019.01); G06F 16/2386 (2019.01); G06F 16/24564 (2019.01); G06F 16/2477 (2019.01); G06F 16/282 (2019.01); G06F 16/285 (2019.01); G06F 16/29 (2019.01); G06F 16/313 (2019.01); G06F 16/35 (2019.01); G06F 16/951 (2019.01); G06N 5/022 (2013.01); G06N 20/00 (2019.01); G06Q 10/101 (2013.01); G06Q 30/0261 (2013.01); G06Q 30/0282 (2013.01); G06Q 50/01 (2013.01); H04L 41/14 (2013.01); H04W 4/02 (2013.01); H04W 4/021 (2013.01); H04W 4/025 (2013.01); H04W 4/029 (2018.02); H04W 4/50 (2018.02); H04W 8/08 (2013.01); H04W 8/16 (2013.01); H04W 8/18 (2013.01); H04W 16/24 (2013.01); H04W 64/00 (2013.01); H04W 64/003 (2013.01); H04W 76/38 (2018.02); H04W 88/02 (2013.01); G06F 16/337 (2019.01); H04W 16/00 (2013.01); H04W 16/30 (2013.01); H04W 16/32 (2013.01); H04W 88/00 (2013.01)] 18 Claims
OG exemplary drawing
 
1. An apparatus comprising:
a processor configured to run one or more modules stored in memory, wherein the one or more modules are configured to:
receive a plurality of pairs of data records;
determine whether one or more pairs of data records are eligible to be clustered, the determination is based upon an analysis of a set of attributes included in the one or more pairs, wherein the analysis is performed by:
converting a first data record in the pair of data records into a first hash;
converting a second data record in the pair of data records into a second hash; and
comparing bits of the first hash and second hash; and
when it is determined that at least one pair of data records can be clustered:
determine a similarity value for the at least one pair of data records based, at least in part, on a plurality of attributes associated with the at least one pair of data records, wherein the similarity value is determined using a machine learning model trained using a supervised learning function operating on ground-truth clusters of data records; and
associate the at least one pair of data records with one or more clusters, each associated with a unique entity, based on the similarity value for the at least one pair of data records.