Automated Document Organization via Predictive File Naming
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Users face tedious and time-consuming tasks when manually renaming and organizing scanned documents, often leading to incorrect storage locations due to repetitive processes.
Innovation Solution
A system that uses a prediction model to automatically name and organize scanned documents by analyzing past document naming patterns and storage locations, suggesting file names and folders based on text and image analysis, with the ability to learn from user corrections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users manually rename and organize scanned documents, then they can control file naming and storage locations, but the process becomes tedious and time-consuming
Solution Approach 1:
The system performs document organization autonomously by analyzing document content through OCR and machine learning models to automatically determine file names and storage locations, eliminating the need for manual user intervention in the organization process
Solution Approach 2:
The patent replaces manual mechanical operations (typing filenames, creating folders, moving files) with automated digital processing using optical character recognition, machine learning algorithms, and programmatic file system operations
2Reliability
If users manually organize documents, then they can store documents in correct locations, but errors occur due to repetitive processes and human forgetfulness
Solution Approach 1:
The system continuously learns from user corrections and feedback to improve its prediction models, allowing it to adapt to changing organization preferences and improve accuracy over time
Solution Approach 2:
The patent replaces human decision-making in document classification with automated machine learning models that analyze document content, metadata, and historical patterns to determine optimal storage locations with high accuracy
3Adaptability or versatility
If users scan and save documents with custom names and locations, then they can organize documents according to personal preferences, but the process must be repeated for each document
Solution Approach 1:
The system performs preliminary analysis of document content and extracts relevant information before the user needs to organize the document, preparing suggested filenames and locations in advance so the user can quickly confirm or make minor adjustments
Solution Approach 2:
The system automatically adapts to user preferences by learning from historical data and correction feedback, providing customized organization suggestions that match individual needs without requiring manual reconfiguration for each document
Data Source
AI summary
A system and method provides automated prediction of filenames and storage locations for scan files generated from a user's scan of their financial documents. A prediction model is generated for the user based on weighted values derived from preexisting filenames and preexisting storage locations for their stored electronic files. Text or images from each scan document is analyzed and weighted and compared to the user's prediction model and a suggested name and storage location is automatically generated. The suggestions are confirmed or corrected by the user prior to storage, and any corrections are used to update the user's prediction model.