US 12,260,070 B2
Systems and methods for generating dynamic interface options using machine learning models
Minh Le, McLean, VA (US); Arturo Hernandez Zeledon, McLean, VA (US); and Rui Zhang, McLean, VA (US)
Assigned to Capital One Services, LLC, McLean, VA (US)
Filed by Capital One Services, LLC, McLean, VA (US)
Filed on Sep. 23, 2020, as Appl. No. 17/029,861.
Prior Publication US 2022/0091713 A1, Mar. 24, 2022
Int. Cl. G06F 3/0484 (2022.01); G06F 3/0481 (2022.01); G06F 9/451 (2018.01); G06F 40/205 (2020.01); G06F 40/279 (2020.01); G06N 3/045 (2023.01); G06N 3/08 (2023.01); G06V 10/40 (2022.01); G06V 30/10 (2022.01)
CPC G06F 3/0484 (2013.01) [G06F 3/0481 (2013.01); G06F 9/451 (2018.02); G06F 40/205 (2020.01); G06F 40/279 (2020.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G06V 10/40 (2022.01); G06V 30/10 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A system for generating dynamic interface options using machine learning models featuring multi-modal feature inputs, the system comprising:
storage circuitry configured to store:
a first machine learning model, wherein the first machine learning model comprises a convolutional neural network; and
a second machine learning model, wherein the second machine learning model performs a Weight of Evidence (WOE) analysis; and
control circuitry configured to:
receive a first user action, from a first user, during a device interface session with a user interface;
determine a first user interface image corresponding to the first user action in the user interface;
determine metadata related to the first user interface image;
retrieve time-dependent user account information for the first user during the device interface session with the user interface;
generate a first feature input based on the metadata;
generate a second feature input based on the time-dependent user account information; and
input the first feature input into the first machine learning model;
input the second feature input into the second machine learning model; and
input/output circuitry configured to:
generate, at the user interface, a dynamic interface option selected by a third machine learning model using an ensemble prediction of outputs from the first machine learning model and the second machine learning model, wherein the dynamic interface option comprises an option to modify an account of the first user.