Context-Aware File Retrieval Using Event Metadata
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Solution Overview
Problem
Conventional information retrieval systems in computers rely on file names and attributes, making it difficult for users to locate files without remembering specific details, as they lack context-based search capabilities.
Innovation Solution
A system and method that utilizes context information related to previous experiences with information items, such as events, to identify and retrieve associated files by indexing and searching context data, including metadata about file usage, applications, and user interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional file system search methods are used (searching by file name, attributes, location), then the search process is simple to implement, but the user cannot locate files when they do not remember the file name or context
Solution Approach 1:
The system performs preliminary actions by automatically capturing and storing context information about file operations (creation, opening, saving, sharing) as events occur. This preliminary collection of contextual data enables users to search for files later using any aspect of that context without having to remember file names or locations.
Solution Approach 2:
The patent introduces context information as an intermediary between the user and the file system. Instead of directly searching for files using traditional methods, users search through context information (what the file was used for, who shared it, when it was created) which then leads to the actual file. This intermediary layer solves the problem of not remembering file names while maintaining simple search operations.
2Productivity
If the system stores and indexes context information for all file operations, then file retrieval capability is significantly improved, but the system complexity increases due to event monitoring, data collection, and indexing mechanisms
Solution Approach 1:
The context information system is designed to be universal and multi-functional, serving multiple purposes: tracking file operations, enabling advanced search capabilities, providing audit trails, and supporting collaboration features. This universal approach consolidates what could be multiple separate systems into one integrated solution, managing complexity while delivering diverse benefits.
Solution Approach 2:
The system implements self-service mechanisms where context information is automatically captured and indexed without requiring manual user input. Event monitors automatically detect file operations, and the indexing system automatically processes and stores context data. This automation reduces the operational complexity of maintaining the system while improving retrieval productivity.
3Measurement precision
If context information is collected and stored for every file operation, then search accuracy is improved, but the quantity of data to be managed and processed increases significantly
Solution Approach 1:
The system extracts only the essential context information needed for effective file retrieval from the vast amount of data generated by file operations. Instead of storing every detail of each file operation, it selectively captures key contextual elements (such as user identity, operation type, time stamps, and relevant metadata) that enable accurate search while minimizing data volume.
Solution Approach 2:
Context information is segmented into distinct categories and types (file operation events, user interactions, metadata) that can be independently managed and indexed. This segmentation allows the system to process and store data in an organized manner, improving search accuracy by enabling targeted queries while reducing the complexity of managing the total data quantity.
Data Source
AI summary
A system and method of collecting information and associated context are provided. Information is retrieved using context information by receiving a search request to identify an information item, the search request including a context comprising circumstantial information related to a previous experience with the information item, and searching at least one data store using the context item, so as to identify the information item associated with the context.