Application Recommendation System Using Auxiliary Information Analysis
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Solution Overview
Problem
The increasing number of applications on smartphones and tablets leads to memory occupation and difficulty in finding specific applications, necessitating an automatic management and recommendation system to enhance user experience.
Innovation Solution
An automatic application management and recommendation method that analyzes auxiliary information using predetermined rules to determine which applications to update, uninstall, or recommend, optimizing system resources and user interface displays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the number of installed applications is increased to provide more functionality, then the versatility of the device is improved, but the memory space occupied increases and system resources are consumed
Solution Approach 1:
The patent extracts and analyzes auxiliary information (usage patterns, device capabilities, event data) from the application ecosystem to identify and recommend applications for removal or updates, thereby freeing memory space while maintaining essential functionality
Solution Approach 2:
The system changes the parameter of application selection by using dynamic auxiliary information analysis instead of static installation lists, enabling intelligent determination of which applications to retain or remove based on actual usage patterns and device state
2Adaptability or versatility
If more applications are installed to meet diverse user needs, then the adaptability is improved, but the difficulty of finding specific applications increases
Solution Approach 1:
The patent implements feedback mechanisms by analyzing user interaction patterns and usage behavior to dynamically generate application recommendations, creating a closed-loop system that learns from user actions and improves application discovery over time
Solution Approach 2:
The system performs self-service by automatically analyzing auxiliary information and generating application recommendations without requiring manual user input, enabling the device to autonomously optimize its application portfolio based on observed usage patterns
3Ease of operation
If manual application management is used to organize and find applications, then the ease of operation is maintained, but the time required for management increases
Solution Approach 1:
The patent enables the system to perform self-service application management by automatically analyzing auxiliary information including usage patterns, device capabilities, and event data to generate recommendations for application updates, removals, and optimizations without requiring manual user intervention
Solution Approach 2:
The patent replaces manual mechanical application management with an automated information processing system that analyzes auxiliary data and generates recommendations, substituting human cognitive effort with computational analysis of usage patterns and device state
Data Source
AI summary
An application recommendation method includes following steps: checking at least one predetermined rule to generate at least one analysis result for at least one of a plurality of candidate applications; and automatically determining an application recommendation result of recommended applications, wherein the at least one of the candidate applications is selectively used as one recommended application in the application recommendation result according to the at least one analysis result. In addition, a computer readable medium stores a program code. When executed by a processor, the program code instructs the processor to perform steps of the application recommendation method. Moreover, a display screen shows an application hot zone according to the application recommendation result of recommended applications.