Natural Language Task Execution in Application Ecosystems
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Solution Overview
Problem
Current application ecosystems require users to have in-depth familiarity with menu-driven user interfaces and navigational workflows, making it cumbersome to access and execute tasks across multiple applications, especially in integrated enterprise systems like human capital management.
Innovation Solution
Implementing a system that uses natural language processing and machine learning classifiers to interpret user requests, generate user interface screens with populated parameters, and execute tasks directly within the application ecosystem, allowing users to perform actions without traditional menu navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional menu-driven user interfaces are used, then users can access tasks across multiple applications, but users require in-depth familiarity with complex interfaces and navigational workflows
Solution Approach 1:
The patent replaces the mechanical menu-driven navigation system with a natural language processing system. Instead of requiring users to navigate through hierarchical menus and understand complex interface structures, the system processes natural language commands to directly execute tasks. This substitution eliminates the need for users to adapt to complex interface patterns while maintaining full task accessibility.
Solution Approach 2:
The patent introduces a natural language processing intermediary between the user and the application ecosystem. This intermediary translates natural language requests into executable tasks, acting as a mediator that eliminates the need for direct interaction with complex menu structures. The intermediary handles the complexity of task execution across multiple applications while presenting a simple natural language interface to users.
2Productivity
If natural language processing is implemented, then users can perform tasks without traditional menu navigation, but the system requires advanced processing capabilities
Solution Approach 1:
The patent implements preliminary action by pre-processing and categorizing natural language commands into standardized task templates. The system anticipates common task patterns and prepares corresponding execution workflows in advance, allowing rapid translation of natural language into actionable tasks. This preliminary structuring of processing paths enables fast task execution while managing system complexity through standardized patterns.
Solution Approach 2:
The patent utilizes parameter changes by transforming natural language input into structured parameters that define task execution. The system identifies and extracts key parameters from natural language requests (such as task type, target application, specific actions) and uses these parameters to dynamically construct execution workflows. This parameter-based approach enables flexible task handling with consistent processing logic.
Data Source
AI summary
Aspects of the present disclosure relate generally to application ecosystems and, more particularly, to navigational and executional operations in an application ecosystem. In embodiments, a method includes: receiving, by a computing device, a natural language request input by a user to perform a task in an application ecosystem of a plurality of applications; determining, by the computing device, an actionable task from the natural language request to perform in the application ecosystem; generating, by the computing device, a user interface screen to perform the task with input parameters required to perform the task populated in elements of the user interface screen derived from the natural language request; and performing the task with the input parameters required in the application ecosystem of the plurality of applications.