Infrequently-Used File Recognition Method for Mobile Storage Cleanup
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Solution Overview
Problem
Conventional methods for recognizing and cleaning trash files on mobile devices inaccurately identify frequently-used cache files, leading to increased response times and incomplete cleanup, as they fail to distinguish between essential and infrequently-used files effectively.
Innovation Solution
A method that scans storage space to identify infrequently-used files by recording and updating last access times, using file attributes to determine non-access duration thresholds, and performing weighted summation of impact values to prompt users for cleanup, ensuring accurate recognition and reduction of storage clutter.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional methods delete cache files to clean storage space, then storage clutter is reduced, but application response time increases and user experience deteriorates
Solution Approach 1:
The patent changes the parameter for file identification from simple 'cache file' classification to multi-dimensional criteria including last access time, file size, file type, and usage frequency. This allows the system to distinguish between truly unnecessary files and frequently-used cache files, deleting only the former while preserving the latter, thus maintaining application response time while reducing storage clutter
Solution Approach 2:
The patent replaces the mechanical/de facto approach of deleting all cache files with a smart selection mechanism based on multiple attributes. Instead of a blanket deletion strategy, the system uses attribute-based filtering (access time, size, type) to intelligently select which files to delete, substituting brute-force cleanup with precision-based file selection
2Measurement precision
If the system records last access time for all files, then file recognition accuracy improves, but system processing overhead increases
Solution Approach 1:
The patent applies local quality by differentiating treatment based on file attributes. Instead of uniformly recording access times for all files, the system selectively records and monitors based on file characteristics (size, type, location). This allows high-precision recognition for important files while reducing processing overhead for less critical files, achieving a balance between accuracy and resource consumption
3Measurement precision
If the system uses multiple file attributes for recognition, then trash file identification accuracy improves, but device complexity increases
Solution Approach 1:
The patent segments the file recognition task into independent attribute evaluations (access time check, size check, type check, frequency check). Each attribute is evaluated separately and contributes to the final decision. This segmentation allows the complex multi-attribute recognition system to be broken down into manageable, independent modules, reducing overall system complexity while maintaining high identification accuracy
Data Source
AI summary
A method for recognizing infrequently-used data includes scanning files in storage space according to a first scanning rule, generating a file set according to the scanned files, for each file in the file set, obtaining a last access time of the file, where the last access time indicates a time when the file was last accessed and not modified, obtaining a file attribute of the file, querying an infrequently-used file recognition condition corresponding to the file attribute, and when the last access time of the file meets the infrequently-used file recognition condition, recognizing the file as an infrequently-used file.