17819781. HEADLESS USER INTERFACE ARCHITECTURE ASSOCIATED WITH AN APPLICATION simplified abstract (Capital One Services, LLC)

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HEADLESS USER INTERFACE ARCHITECTURE ASSOCIATED WITH AN APPLICATION

Organization Name

Capital One Services, LLC

Inventor(s)

Andrew Ricchuiti of Dallas TX (US)

James Dunlap of The Colony TX (US)

Christopher Brown of Dallas TX (US)

HEADLESS USER INTERFACE ARCHITECTURE ASSOCIATED WITH AN APPLICATION - A simplified explanation of the abstract

This abstract first appeared for US patent application 17819781 titled 'HEADLESS USER INTERFACE ARCHITECTURE ASSOCIATED WITH AN APPLICATION

Simplified Explanation

The patent application describes a system that uses machine learning to determine the target environment and user interface for accessing information associated with an application on a user device.

  • System receives a request from a user device to access application information.
  • Request includes user device data indicating characteristics of a particular use.
  • Machine learning model is used to analyze historical data of application usage.
  • Output from the model provides target environment for the user device.
  • Target user interface corresponding to the target environment is identified.
  • UI data corresponding to the target UI is transmitted to the user device.

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      1. Potential Applications
  • Personalized user interfaces for applications based on user device characteristics.
  • Adaptive user interfaces that change based on historical usage patterns.
      1. Problems Solved
  • Providing a seamless and personalized user experience for accessing application information.
  • Adapting user interfaces to different user devices and environments.
      1. Benefits
  • Improved user experience with tailored interfaces.
  • Increased efficiency in accessing application information.
  • Better utilization of machine learning for user interface optimization.


Original Abstract Submitted

In some implementations, a system may receive, from a user device, a request to access information associated with the application. The request may include user device data indicating characteristic(s) associated with a particular use of the user device. The system may provide the user device data as input to a machine learning model, which may be trained based on historical data associated with historical usage of the application by the user device and/or other user devices. The system may receive, as an output from the machine learning model, a target environment associated with the user device. The system may identify a target user interface (UI) associated with the information associated with the application. The target UI may correspond to the target environment. The system may transmit, to the user device, UI data corresponding to the target UI.