Digital Action Interface Selection for Resource-Aware Assistant Execution
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Solution Overview
Problem
Existing systems face inefficiencies in selecting an interface or mode of execution for digital actions, leading to excessive resource consumption and underutilization of digital assistants due to lack of awareness of relevant functions they can perform on third-party applications, resulting in suboptimal and wasteful user interactions.
Innovation Solution
A system that dynamically selects an interface and mode of execution for digital actions based on device properties and historical engagement, identifying relevant functions of digital assistants and providing platform-specific action linking to efficiently execute these actions, optimizing resource usage and user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a rich interface with multiple digital assistant functions is provided, then user capability and functionality are improved, but resource consumption and device complexity increase
Solution Approach 1:
The patent applies local quality by providing different interface types (rich vs. limited) to different devices based on their specific capabilities. The system evaluates device properties and historical engagement to determine which devices receive access to full digital assistant functionality versus limited functionality, ensuring each device receives appropriate resources matched to its capabilities.
Solution Approach 2:
The system dynamically adjusts the interface type and digital assistant functionality provided to each device based on real-time evaluation of device properties and historical engagement data. This dynamic adaptation allows the system to optimize resource allocation by providing richer interfaces to capable devices and simpler interfaces to resource-constrained devices.
2Adaptability or versatility
If a rich interface with multiple digital assistant functions is provided, then user capability and functionality are improved, but device complexity increases
Solution Approach 1:
The patent implements local quality by tailoring interface complexity to match device capabilities. The system provides simplified interfaces to devices with limited processing power or memory, while offering rich, feature-complete interfaces to devices with adequate resources, thereby reducing overall system complexity without sacrificing functionality where available.
3Use of energy by moving object
If interface selection is optimized for resource efficiency, then resource consumption is reduced, but adaptability to different device capabilities may worsen
Solution Approach 1:
The system dynamically selects interface types based on real-time evaluation of device properties and historical engagement patterns. This dynamic approach ensures optimal resource utilization while maintaining adaptability, as the system can provide rich interfaces to capable devices and simplified interfaces to constrained devices, with the ability to adapt as device capabilities or usage patterns change.
Solution Approach 2:
The patent implements universality by creating a multi-functional interface selection system that can provide different types of interfaces (rich interface, limited interface) through a single unified framework. This allows the system to adapt to various device capabilities while maintaining a consistent underlying architecture, ensuring broad compatibility across different device types.
Data Source
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AI summary
Interface and mode selection for digital action execution is provided. For example, a system loads a script library embedded in an electronic resource. The system determines a historic level of engagement between a client computing device and one or more digital assistants. The system selects, based on a first property of the client computing device and the historic level of engagement, a type of digital interface. The system generates, based on the type of digital interface, a digital interface with the call-to-action. The system determines, responsive to an instruction to execute the call-to-action, a mode of execution. The system selects a digital assistant and a second client device to execute the call-to-action. The system transmits the call-to-action to the second client device for execution.