US 12,450,206 B2
Methods and systems for providing database development recommendations based on multi- modal correlations detected through artificial intelligence
Steve Cheng, Exton, PA (US); and Narender Pashikant, Ashburn, VA (US)
Assigned to Capital One Services, LLC, McLean, VA (US)
Filed by Capital One Services, LLC, McLean, VA (US)
Filed on Jun. 10, 2024, as Appl. No. 18/738,743.
Application 18/738,743 is a continuation of application No. 17/590,471, filed on Feb. 1, 2022, granted, now 12,007,958.
Prior Publication US 2024/0330250 A1, Oct. 3, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06F 16/21 (2019.01); G06F 11/34 (2006.01); G06F 16/2458 (2019.01)
CPC G06F 16/211 (2019.01) [G06F 11/3442 (2013.01); G06F 11/3457 (2013.01); G06F 16/2462 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A system for providing database development recommendations, the system comprising:
cloud-based storage circuitry storing a plurality of machine learning models; and
cloud-based control circuitry configured to:
determine, based on a parameter determined using user criteria comprising static data and expected dynamic data for a database on a network of computing devices, a first subset of static and dynamic training data for generating a feature input, wherein the first subset of static and dynamic training data comprises data streamed in real time from databases accessible to the network of computing devices;
input the feature input into a machine learning model to generate an output;
select a database design element from a plurality of database design elements based on the output; and
generate a database development recommendation based on the database design element.