Dynamic Window Grouping for Mobile Multi-Window Management
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In multi-window systems, especially on small information-processing devices like mobile phones without a pointing device, managing multiple windows for display or hiding becomes complex and inefficient, as existing techniques rely on pre-determined groupings or transition-based controls, which do not account for actual user usage patterns.
Innovation Solution
Implementing a system with a control means to measure the duration of simultaneous display or data exchange between windows, allowing for dynamic display control based on measured time or data amounts, enabling a single instruction to display or hide windows that are frequently used together, thereby simplifying user operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a user manually manages multiple windows on a small information-processing device without a pointing device, then the device can display multiple windows, but the operation complexity increases significantly
Solution Approach 1:
The system automatically determines which windows to display together based on data exchange relationships, eliminating the need for manual user grouping. The window management system serves itself by autonomously analyzing inter-window data dependencies and making display decisions without requiring complex user interactions or pre-defined grouping configurations.
Solution Approach 2:
The window grouping is not fixed but dynamically determined based on real-time data exchange relationships. The system continuously monitors which windows exchange data and automatically adjusts the displayed window combinations accordingly, making the window management adaptive to changing usage patterns rather than relying on static pre-defined groups.
2Ease of operation
If windows are grouped in advance for display control, then window display management becomes systematic, but the system cannot adapt to different usage scenarios requiring different groupings
Solution Approach 1:
The system transitions from static pre-defined groupings to dynamic determination of window groups based on actual data exchange relationships. The window associations are continuously updated as data exchange patterns change, allowing the system to adapt to different usage scenarios automatically without requiring users to reconfigure groupings.
Solution Approach 2:
The system monitors data exchange between windows and uses this feedback information to automatically determine which windows should be displayed together. This closed-loop approach allows the system to learn from actual usage patterns and adjust window groupings accordingly, providing both systematic control and adaptability to different scenarios.
3Adaptability or versatility
If all windows are displayed simultaneously, then all applications are accessible, but the display area is insufficient and user focus is diluted
Solution Approach 1:
The system extracts and displays only the subset of windows that have active data exchange relationships, separating them from other windows. This selective extraction approach ensures that the limited display area is dedicated to windows that are currently relevant to each other, maintaining application accessibility while optimizing display space utilization.
Solution Approach 2:
Different window combinations are displayed in different contexts based on their specific data exchange relationships. Rather than a uniform display approach, the system applies local quality by tailoring the displayed window set to the specific inter-window data relationships, ensuring that each display configuration is optimized for its particular usage scenario.
4Adaptability or versatility
If windows are frequently switched between, then multiple applications can be used, but the time and operations required increase
Solution Approach 1:
The system performs preliminary analysis of data exchange relationships to proactively determine which windows should be displayed together before the user needs to switch between them. By pre-establishing these associations based on monitored data patterns, the system reduces the time and operations required for window switching, as relevant windows are already positioned for immediate access.
Data Source
AI summary
To simplify an operation for displaying or hiding windows, depending on a user or usage by the user. An information-processing device, according to the present invention, stores for each window, a time during which the window has been displayed together with another window (simultaneous display time), as a relevance table. The information-processing device, when receiving an instruction to display a window (subject window), refers to a relevance table for the subject window to identify a window whose simultaneous display time is the longest (simultaneous display window), and displays the subject window and the simultaneous display window. Also, the information-processing device, when receiving an instruction to hide a subject window, hides the subject window and a simultaneous display window.