Contextual Application Card Prediction for Mobile Switching
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Solution Overview
Problem
Mobile computing devices face inefficiencies in switching between applications, requiring users to manually navigate through multiple steps, leading to increased time consumption, wear and tear on devices, and higher power consumption due to the exponential growth of applications, making it challenging to discover application functions and their corresponding views.
Innovation Solution
A system that uses a server to analyze contextual data from a mobile computing device, predicting the next user intent and displaying an application card concurrently with the current application view, allowing users to access the next application function without manual navigation by executing computer-readable instructions stored in card objects that include GUI elements and function parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users manually navigate through multiple steps to switch between applications, then application switching functionality is achieved, but time consumption increases and productivity decreases
Solution Approach 1:
The system performs preliminary actions by analyzing contextual data (sensor measurements, application usage history, current application state) to predict the user's next intended application before the user actually switches. This allows the system to prepare and display the predicted application card in advance, so when the user taps the card, the application is already ready to launch, significantly reducing the time required for application switching.
Solution Approach 2:
The patent introduces an intermediary element - the application card - that acts as a mediator between the current application and the target application. Instead of directly switching from one application to another through multiple manual steps, the user interacts with the intermediate card object that contains executable instructions and GUI elements, which then facilitates the transition to the predicted application, streamlining the switching process.
2Ease of operation
If users manually navigate through multiple steps to switch between applications, then application switching is possible, but device wear and tear increases
Solution Approach 1:
The system extracts the essential functionality needed for application switching from the complex multi-step navigation process. By analyzing contextual data and predicting user intent, the system extracts only the necessary information to display the predicted application card, eliminating unnecessary intermediate steps and simplifying the user interaction to a single tap gesture.
Solution Approach 2:
The system changes the parameter of interaction complexity by transforming the traditional multi-step navigation sequence into a single-step card-based interaction. The application card object encapsulates multiple functions (displaying application information, predicting next application, enabling direct launch) into a single interactive element, reducing the number of user actions required from multiple steps to just one tap.
3Productivity
If users manually navigate through multiple steps to switch between applications, then application switching functionality is achieved, but power consumption increases
Solution Approach 1:
The system performs preliminary analysis of contextual data including sensor measurements and application usage history to predict the next application before the user initiates the switch. This preliminary action allows the system to prepare the application card and pre-load necessary resources, reducing the computational work required during the actual switching moment and thereby lowering overall power consumption while maintaining fast application access.
4Adaptability or versatility
If the system displays application cards based on contextual data analysis, then application discovery is enhanced, but system complexity increases
Solution Approach 1:
The application card object serves multiple functions simultaneously: it displays application information, predicts user intent based on contextual analysis, provides navigation capabilities, and enables direct application launch. By making the card object multi-functional, the system enhances application discovery and versatility without proportionally increasing complexity, as a single object handles multiple tasks that would otherwise require separate components.
Data Source
AI summary
A server includes a network communication device, a storage device, and a processing device. The processing device executes computer-readable instructions that, when executed by the processing device, cause the processing device to: receive contextual data from a client computing device via the network communication device, the contextual data indicates a first application view displayed on the client computing device; identify a first application function ID that identifies a first application function corresponding with the first application view; determine a first user intent ID that corresponds with the first application function ID; determine a second user intent ID that transitions from the first user intent ID; identify a second application function ID that corresponds with the second user intent ID; retrieve a card object corresponding with the second application function ID from the storage device; and transmit the card object to the client computing device via the network communication device.