Modular Space Composition for Intent-Ranked Unified Interfaces
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Solution Overview
Problem
Existing systems require inefficient interaction with multiple user interfaces and applications to accomplish real-world tasks, leading to redundant user inputs and network transmissions, as users often lack knowledge of relevant applications or services for their needs.
Innovation Solution
A system that generates modular spaces by integrating functionalities from various applications based on user intent, using machine-learned models to rank and compose components, allowing for streamlined interfaces and efficient resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users interact with multiple separate applications to accomplish real-world tasks, then each application can provide specialized functionality, but users must perform redundant inputs and network transmissions across multiple interfaces
Solution Approach 1:
The patent combines multiple application functionalities into a single unified interface that can perform real-world tasks by integrating components from different applications. The system merges weather data, news feeds, messaging capabilities, and other functions into one cohesive workspace, eliminating the need for users to switch between multiple applications and reducing redundant inputs.
Solution Approach 2:
The unified interface is designed to perform multiple functions simultaneously by dynamically integrating relevant components based on user intent. The system can adapt to different task types (weather checking, news browsing, communication) within a single interface, providing universal access to various functionalities without requiring separate application interactions.
2Adaptability or versatility
If users interact with multiple separate applications, then each application can operate independently, but network transmissions are repeated across multiple interfaces
Solution Approach 1:
The system merges network communication operations by consolidating data requests through a single interface. Instead of each application making separate network calls, the unified interface aggregates data needs and performs network transmissions once, then distributes the retrieved information to relevant components, significantly reducing bandwidth consumption.
Solution Approach 2:
The unified interface acts as an intermediary between the user and multiple underlying applications/services. It mediates network communications by centralizing data retrieval operations, caching results, and distributing information to relevant components, thereby eliminating redundant network transmissions while maintaining independent application functionalities.
3Ease of operation
If the system integrates multiple applications into a unified interface, then user input efficiency improves, but the system complexity increases
Solution Approach 1:
The system segments the complex integration task into manageable components by maintaining independent functional modules from various applications. Each component remains separately developed and managed, but the unified interface orchestrates them through standardized interfaces, reducing overall system complexity while improving user input efficiency.
Solution Approach 2:
The unified interface serves as an intermediary layer that manages the complexity of integrating multiple applications. It provides a standardized communication protocol and data flow management system that simplifies the interaction between diverse components, hiding the underlying complexity from users while maintaining efficient operation.
4Productivity
If the system dynamically composes modular spaces based on user intent, then processing efficiency improves, but computational resources for intent analysis increase
Solution Approach 1:
The system performs preliminary intent analysis by pre-processing user inputs and predicting required components before full task execution. It uses machine learning models to anticipate user needs and pre-load or pre-position relevant components, reducing the computational burden during actual task execution while maintaining high productivity.
Solution Approach 2:
The system performs partial intent analysis by focusing computational resources on the most critical aspects of user intent rather than complete analysis. It uses heuristic methods to identify key task requirements and compositions relevant components without exhaustive processing, reducing energy consumption while maintaining effective task completion.
Data Source
AI summary
Example embodiments of the present disclosure provide for an example method including obtaining component data associated with a plurality of components. The example method includes generating an index of the component data and obtaining user input data indicative of a request. The example method includes processing the user input data to determine an intent associated with the request and obtaining, based on the intent, data indicative of one or more components from the index. The example method includes determining a rank for at least one respective component of the one or more components. The example method includes updating a user interface to display the one or more components, wherein the components are displayed based at least in part on the rank of the respective component. The example method can include generating modular spaces composed of a plurality of components to generate composite application interfaces which can include cross-application functionalities.