Keyword-Based Data Management for Automated Backup
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Solution Overview
Problem
Traditional backup software treats all data equally, failing to differentiate between sensitive and valuable files, making it inefficient for users to manage and protect their data, and requiring frequent user interaction for mundane tasks like disc insertion or network connections.
Innovation Solution
A method that uses keywords to categorize and manage data, allowing for automatic identification and organization of files based on personal information, enabling targeted backup, synchronization, and management across different storage locations without requiring specific file formats or locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional backup software treats all data equally, then the backup process is simple to implement, but the efficiency of data protection is reduced because valuable and sensitive files cannot be differentiated
Solution Approach 1:
The system automatically analyzes file contents, extracts keywords, and categorizes data without requiring user intervention. The backup software performs self-service by autonomously identifying valuable files and determining appropriate backup strategies based on extracted keywords, eliminating the need for manual file assessment while improving protection efficiency
Solution Approach 2:
The system changes the parameter of file identification from traditional metadata-based classification to content-based keyword extraction. By analyzing file contents and extracting meaningful keywords, the system transforms how files are categorized and prioritized for backup, enabling differentiated protection without proportionally increasing system complexity
2Ease of operation
If backup software requires periodic user interaction for disc insertion or network connection, then the system can adapt to user needs, but the ease of operation deteriorates because users must perform unwanted chores
Solution Approach 1:
The system performs automatic keyword extraction and file categorization without requiring user initiation or intervention. The backup process autonomously monitors for new files, extracts keywords, determines categorization, and executes backup actions without user interaction, significantly improving ease of operation while maintaining high automation levels
Solution Approach 2:
The system performs preliminary keyword extraction and file analysis before the actual backup operation. By pre-processing files to extract keywords and determine categorization in advance, the system prepares backup strategies proactively, eliminating the need for user intervention during the backup process itself
3Loss of information
If all files are stored in the same location without organization, then the storage system is simple to manage, but the loss of information increases because users cannot easily locate and assess desired storage destinations
Solution Approach 1:
The system segments the storage system into multiple categorized locations based on extracted keywords. Files are automatically divided into different storage destinations according to their keyword-based categorization (e.g., personal, business, sensitive), enabling users to easily locate files by type while the system manages the organizational complexity automatically
Solution Approach 2:
The keyword extraction and categorization system acts as an intermediary between files and storage locations. Rather than directly mapping files to storage destinations, the system introduces keyword-based categorization as an intermediate layer that automatically determines appropriate storage locations, reducing both information loss and user management burden
Data Source
AI summary
A method, implementable in a system coupled to a network, includes accessing a first portion of a memory device coupled to the network. The first portion has stored thereon information characterizing an entity. An information set of a predetermined information type is gathered from the first portion. First and second information subsets of the information set are organized into first and second keywords. A second portion of a memory device coupled to the network is accessed. The second portion has stored thereon a plurality of data sets. First and second subsets of the data sets are identified. Each data set of the first data-set subset includes the first keyword, and each data set of the second data-set subset includes the second keyword. The first data-set subset is stored in a third portion of a memory device coupled to the network.