Context-Aware Application Icon Prioritization for Mobile Launchers
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Solution Overview
Problem
As the number of applications on mobile information terminals increases, users face difficulty in finding intended applications and navigating the necessary operation processes, leading to decreased convenience in utilizing application programs.
Innovation Solution
An information processing device that acquires current user situation data, including date, time, and position, to select and prioritize applications based on user history, similar user data, and predictive models, optimizing the display and activation of applications on the screen.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the number of applications installed into the mobile information terminal is increased, then the functionality and versatility of the terminal is improved, but it becomes difficult for a user to find an intended application or operation processes necessary for activation are increased
Solution Approach 1:
The system performs preliminary actions by acquiring user profile information, application use history, and current situation data (date, time, position) before the user needs to find an application. A prediction model is pre-built and trained on historical data to automatically determine which application should be presented next, eliminating the need for users to search through a long list of applications.
Solution Approach 2:
The system provides self-service by automatically selecting and presenting applications based on analyzed user behavior patterns and current context. The prediction model autonomously determines application selection without requiring user input or manual searching, with the system serving itself by proactively presenting relevant applications based on learned user preferences.
2Adaptability or versatility
If the number of applications installed into the mobile information terminal is increased, then the functionality and versatility of the terminal is improved, but the operation processes necessary for activation of an intended application are increased
Solution Approach 1:
The system performs preliminary actions by acquiring user profile information, application use history, and current situation data (date, time, position) before the user needs to find an application. A prediction model is pre-built and trained on historical data to automatically determine which application should be presented next, eliminating the need for users to search through a long list of applications.
Solution Approach 2:
The system utilizes feedback from user behavior patterns, application use history, and current situation data to continuously refine the prediction model. This feedback loop enables the system to learn from actual user interactions and improve its accuracy in predicting which applications users want to access, thereby reducing activation time in the future.
Data Source
AI summary
The present technology relates to an information processing device, an information processing method, and a program with which convenience of a user in utilization of an application program can be improved.An information acquisition unit acquires first information indicating a current situation including a current date and time and a current position of a user. A selection unit selects a presented application, which is an application program presented to a user, on the basis of a use history, a profile of the user, and the first information, the use history being a use history of an application program of a user and including second information indicating a situation in activation which situation includes a date and time and a position of the user in activation of each application program. The present technology can be applied, for example, to a device or a program that controls a display on a lock screen or a launcher screen.