US 11,989,207 B2
Methods and systems for synchronizing communication records in computer networks based on detecting patterns in categories of metadata
Aditya Pai, Brooklyn, NY (US); Brice Elder, Allen, TX (US); Niyati Shah, Pleasanton, CA (US); and Marek Sedlacek, San Francisco, CA (US)
Assigned to Capital One Services, LLC, McLean, VA (US)
Filed by Capital One Services, LLC, McLean, VA (US)
Filed on Mar. 3, 2023, as Appl. No. 18/178,468.
Application 18/178,468 is a continuation of application No. 17/098,039, filed on Nov. 13, 2020, granted, now 11,630,843.
Prior Publication US 2023/0205787 A1, Jun. 29, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 16/27 (2019.01); G06F 16/182 (2019.01); G06F 16/215 (2019.01); G06F 16/2455 (2019.01)
CPC G06F 16/273 (2019.01) [G06F 16/182 (2019.01); G06F 16/215 (2019.01); G06F 16/2456 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A system for synchronizing communication records in computer networks based on detecting patterns in categories of metadata, the system comprising:
one or more processors; and
a non-transitory, computer-readable medium storing instructions that, when executed by the one or more processors, cause operations comprising:
retrieving first user record data for a first user from a first network, wherein the first user record data comprises a first set of metadata for a first set of communications of the first user during a predetermined time period, and wherein the first set of metadata comprises a respective set of field categories for each communication of the first set of communications;
retrieving second user record data for the first user, wherein the second user record data comprises a second set of metadata for a second set of communications of the first user during the predetermined time period, and wherein the second set of metadata comprises the respective set of field categories for each communication of the second set of communications;
generating a first set of patterns for the first set of metadata and a second set of patterns for the second set of metadata, wherein each pattern in the first set of patterns and the second set of patterns comprises a combination of corresponding values within respective field categories;
inputting the first set of patterns and the second set of patterns into a machine learning model, wherein the machine learning model determines a likelihood that a first pattern of the first set of patterns matches a second pattern from the second set of patterns, and wherein the first pattern is not identical to the second pattern;
based on receiving, from the machine learning model, matching patterns from the first set of patterns and the second set of patterns, identifying a first communication of the first set of communications that matches a second communication of the second set of communications; and
generating for display, on a user interface, a recommendation based on determining that the first communication and the second communication correspond to a single communication.