Document Hierarchy Permissioning for Accurate File Sharing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Managing electronic document databases is tedious and time-consuming due to the difficulty in determining appropriate document permissions for sharing, especially when documents are created without predefined categories, leading to issues with incorrect or incomplete sharing with users such as advisors.
Innovation Solution
A system and method for determining document permissions using a permissions database that identifies users, document categories, and routing actions to automatically assign permissions, utilizing machine learning and rule-based models to suggest and apply permissions based on document metadata and content analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If documents are created without predefined permission categories, then document creation is simplified and faster, but document permission management becomes difficult and errors increase
Solution Approach 1:
The system performs preliminary action by automatically assigning permission categories and metadata to documents at the time of creation. The machine learning model analyzes document content and assigns appropriate categories before the document is stored, ensuring permission accuracy is established in advance rather than requiring manual intervention later.
Solution Approach 2:
The system enables self-service by using machine learning models to automatically determine document permissions without requiring manual input from users. The system independently analyzes document content, identifies appropriate categories, and assigns permissions automatically, freeing users from manual permission management while maintaining accuracy.
2Reliability
If manual document permission assignment is used, then permission accuracy can be maintained, but time consumption and labor effort increase significantly
Solution Approach 1:
The system replaces the mechanical manual process of permission assignment with an automated machine learning-based system. Instead of requiring users to manually review and assign permissions, the system uses AI models to automatically analyze document content and assign appropriate permissions, significantly reducing time while maintaining accuracy.
Solution Approach 2:
The machine learning model performs self-service by independently analyzing document content and automatically assigning permissions without human intervention. The system processes documents autonomously, making decisions about permission categories based on learned patterns from document content and metadata.
3Productivity
If automated permission assignment is implemented, then time consumption is reduced, but system complexity increases
Solution Approach 1:
The machine learning model acts as an intermediary between the document and the permission system. It receives documents, analyzes their content, and translates them into appropriate permission categories and metadata, simplifying the overall system architecture by introducing a dedicated intermediate layer that handles complexity.
Solution Approach 2:
The system substitutes complex manual permission management with a machine learning-based automated system. While the underlying AI model is complex, it encapsulates this complexity in a single service layer, presenting a simple interface to users while handling the computational complexity internally.
4Adaptability or versatility
If documents are shared with multiple users, then collaboration is improved, but incorrect sharing errors increase
Solution Approach 1:
The system performs preliminary action by automatically determining and assigning correct permission categories and metadata to documents before sharing. This preliminary classification ensures that when documents are shared with multiple users, the system can accurately determine who should have access based on pre-established categories and user roles.
Solution Approach 2:
The machine learning model enables self-service by automatically determining appropriate sharing permissions without requiring manual review. The system independently analyzes document content, identifies correct categories, and automatically assigns permissions to appropriate users, reducing human error in the sharing process.
Data Source
AI summary
Provided herein are systems, methods, and computer readable media for document hierarchy permissions. This may include providing a permission database comprising a plurality of users, a plurality of advisors, and a plurality of categories. A candidate document is received at a network device. A candidate user, a candidate routing action, and a candidate document category are identified from the candidate document. A candidate document permission attribute is generated identifying the candidate user, candidate file location, and the candidate document category. The candidate document is stored, and the candidate document permission attribute corresponding to the candidate document is stored.