Compound Action Links in Multi-Modal Networked Environments
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Solution Overview
Problem
Conventional macroinstructions in computing are complex and often require sophisticated users to create, are application-specific or application-agnostic, and fail to effectively map long sequences of user commands to single actions in multi-modal networked environments, limiting their usability and accessibility.
Innovation Solution
A data management server that automatically tracks and identifies frequent sequences of digital actions, generating compound actions and deep links as UI elements or voice commands, allowing users to execute complex tasks with a single action or voice command.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional macroinstructions are used to map long sequences of user commands to single actions, then task automation is improved, but the complexity of creating and managing these macroinstructions increases significantly
Solution Approach 1:
The system automatically generates compound actions by monitoring and analyzing user interactions with digital devices. Instead of requiring users to manually program macroinstructions, the system self-services by observing repeated action sequences and automatically creating compound actions that represent these sequences, thereby resolving the contradiction between task automation and complexity.
Solution Approach 2:
The system performs preliminary analysis of user interaction patterns before generating compound actions. By monitoring and storing sequences of actions in advance, the system prepares the groundwork for automatic compound action generation, allowing efficient task automation without requiring users to pre-program complex macroinstructions.
2Productivity
If macroinstructions are manually programmed by sophisticated users, then application-specific automation is achieved, but accessibility to ordinary users is reduced
Solution Approach 1:
The system eliminates the need for users to program macroinstructions by automatically generating compound actions from observed usage patterns. This self-service approach makes advanced automation accessible to ordinary users without requiring programming knowledge, while still achieving application-specific automation tailored to individual user behaviors.
Solution Approach 2:
The system continuously monitors user interactions and uses this feedback to automatically refine and generate compound actions. By incorporating real-time feedback from actual usage patterns, the system adapts to user needs and creates personalized automation without requiring user intervention or programming expertise.
3Productivity
If compound actions are automatically generated for every repeatable sequence, then task efficiency is improved, but the burden of memorizing numerous inputs increases
Solution Approach 1:
The system creates a universal interface where a single compound action can represent multiple related tasks. By designing compound actions that capture essential task patterns rather than every possible variation, the system reduces the number of inputs users need to memorize while maintaining high task efficiency across diverse applications.
Solution Approach 2:
The system generates compound actions for the most frequently repeated and impactful action sequences, rather than attempting to automate every possible task sequence. This selective approach ensures that users benefit from automation for high-value tasks without being overwhelmed by an excessive number of compound actions to memorize.
4Measurement precision
If macroinstructions are application-specific, then precision for particular tasks is improved, but versatility across different applications is reduced
Solution Approach 1:
The system dynamically generates compound actions tailored to each user's specific application usage patterns. Rather than using static, pre-defined macroinstructions, the system adapts compound actions to match the user's actual workflows across different applications, achieving both task precision and application versatility through dynamic adaptation.
Solution Approach 2:
The system changes the parameters of compound actions based on the specific application context and user behavior patterns. By adjusting the characteristics of compound actions according to different applications and tasks, the system maintains high precision for particular tasks while remaining versatile across diverse applications.
Data Source
AI summary
A method comprises determining a threshold based on a shape or size of a graphical user interface (GUI); selecting one or more sequences of digital actions (actions) as one or more compound actions from a list of sequences of actions, the one sequence of actions being performed by multiple computer devices of a plurality of computer devices, including at least one input device and at least one output device, the one or more sequences of actions having a total number of sequences that is no more than the threshold and satisfying a set of criteria related to a number of actions in each sequence of actions; creating a deep link as a shortcut representing a specific compound action, the shortcut when invoked causing performing the specific compound action and producing a specific result; causing presenting the shortcut as an UI element in the GUI.