Systems and methods for using machine learning models to organize and select modular components for user interface templates
AssigneeCapital One Services, LLC
InventorsMark Morrison, Andrew Ricchuiti, Briana Shaver, Erin Edwards
Life of this patent
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Abstract
Methods and systems for using machine learning models to organize and select modular components for user interface templates. For example, the methods and systems may use machine learning and/or artificial intelligence to generate user interfaces with a preferred number of user input fields and/or pages, in which the preferred number both satisfies any requirements for the user interface (e.g., information, categories of information, etc.), and ensures that all privacy concerns are met.
Claims20
A system for using machine learning models to organize and select modular components for user interface templates, the system comprising:
- cloud-based storage circuitry for storing a user profile corresponding to a user account;
- cloud-based control circuitry for:
- retrieving the user profile corresponding to the user account, wherein the user profile includes a behavior characteristic, and wherein the behavior characteristic indicates likely user behavior when interacting with user interfaces;
- determining template requirements for a user interface, wherein the template requirements include a plurality of predetermined categories of information about a user that is required;
- generating a first feature input based on the user profile and the template requirements;
- inputting the first feature input into a machine learning model, wherein the machine learning model is trained to determine a plurality of categories of account characteristics required to be populated to meet the template requirements;
- receiving from the machine learning model a first output, wherein the first output indicates, based on the first feature input, a preferred number of user input fields and a preferred number of user interface pages;
- and
- cloud-based control circuitry for generating for display, on a user device, the user interface comprising the preferred number of user input fields and the preferred number of user interface pages, wherein the preferred number of user input fields are arranged as modular components on each page of the preferred number of user interface pages.
A method for using machine learning models to organize and select modular components for user interface templates, the method comprising:
- retrieving a user profile corresponding to a user account for a user, wherein the user profile includes a behavior characteristic, and wherein the behavior characteristic indicates likely user behavior when interacting with user interfaces;
- determining template requirements for a user interface;
- generating a first feature input based on the user profile and the template requirements;
- inputting the first feature input into a machine learning model, wherein the machine learning model is trained to determine a number of user input fields or a number of user interface pages based on known behavior characteristics for user accounts retrieved from user profiles;
- receiving from the machine learning model a first output, wherein the first output indicates, based on the first feature input, a preferred number of user input fields and a preferred number of user interface pages;
- and
- generating for display, on a user device, the user interface comprising the preferred number of user input fields and the preferred number of user interface pages.
A non-transitory, computer readable medium for using machine learning models to organize and select modular components for user interface templates comprising instructions that when executed on one or more processors cause operations comprising:
- retrieving a user profile corresponding to a user account for a user, wherein the user profile includes a behavior characteristic, and wherein the behavior characteristic indicates likely user behavior when interacting with user interfaces;
- determining template requirements for a user interface;
- generating a first feature input based on the user profile and the template requirements;
- inputting the first feature input into a machine learning model, wherein the machine learning model is trained to determine a number of user input fields and a number of user interface pages based on known behavior characteristics for user accounts retrieved from user profiles;
- receiving from the machine learning model a first output, wherein the first output indicates, based on the first feature input, a preferred number of user input fields and a preferred number of user interface pages;
- and
- generating for display, on a user device, the user interface comprising the preferred number of user input fields and the preferred number of user interface pages.
Dependencies are inferred from the claim text.