File Importance Classification for Dynamic Policy Assignment
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Solution Overview
Problem
Existing information management systems lack the ability to dynamically and efficiently classify files based on their relative importance, leading to inefficient resource utilization and inconsistent data backup, archiving, and security policies across different file types.
Innovation Solution
The implementation of an Importance Classifier Engine (ICE) and an Information Management Policy Engine (MPE) that determine and apply customized backup, archiving, and security policies to files based on their relative importance, which is calculated using parameters such as author, sharing, uniqueness, and keyword presence, allowing for differential treatment of files.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a common information management policy is applied to all files, then implementation simplicity is maintained, but resource utilization efficiency deteriorates
Solution Approach 1:
The patent applies local quality by differentiating information management policies based on file characteristics. The system evaluates each file's importance, type, and access patterns to assign customized backup frequencies, retention periods, and storage locations, rather than applying a uniform policy to all files. This enables efficient resource allocation where critical files receive enhanced protection while less important files use minimal storage resources.
2Productivity
If file-based differentiation is implemented, then resource utilization efficiency improves, but system complexity increases
Solution Approach 1:
The patent implements self-service by enabling files to automatically classify themselves into importance categories based on predefined criteria such as file type, access frequency, and user-defined tags. The system autonomously evaluates files and assigns appropriate management policies without requiring manual intervention or complex administrative configuration, thereby reducing system complexity while maintaining differentiated resource allocation.
3Measurement precision
If manual policy configuration is used, then policy precision is achieved, but operational efficiency deteriorates
Solution Approach 1:
The patent applies preliminary action by pre-defining multiple information management policy templates with specific parameters for backup frequency, retention periods, and storage locations. These templates are prepared in advance and automatically matched to files based on their characteristics, eliminating the need for manual policy configuration for each file while maintaining precise control over data management strategies.
Data Source
AI summary
The relative importance of a file is determined based on an importance parameter and an information management policy is caused to be applied to the file based on the determined relative importance of the file. The importance parameter may be the author of the file, the number of users with whom the file is shared, the relationship between the users with whom a file is shared, the uniqueness of the file, or the presence of particular keywords in the file.