File Name Pattern Mapping for Automated Document Categorization
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Solution Overview
Problem
Software applications require users to manually verify and categorize numerous electronic documents, which is time-consuming and prone to human error, especially when dealing with hundreds or thousands of documents of different types.
Innovation Solution
The system automates the categorization and data entry process by analyzing file names to identify segments of characters that correspond to categories, allowing for simultaneous categorization and updating of multiple documents without user interaction, using a dynamic keyboard for defining mapping patterns and displaying category values in the user interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually verify and categorize electronic documents through a user interface, then data accuracy can be ensured through user verification, but the process becomes extremely time-consuming when dealing with hundreds or thousands of documents
Solution Approach 1:
The system performs preliminary categorization by analyzing file names before documents need to be processed. File name patterns are pre-defined with mapping rules that automatically extract category information, so when documents are uploaded, their categories are already determined without requiring manual verification for each document
Solution Approach 2:
The system enables self-service automation where the software automatically categorizes documents based on file name analysis without requiring user intervention. The mapping between file name patterns and category values is configured once and then the system autonomously performs categorization for all documents
2Reliability
If users manually enter data for each document through the user interface, then each document can be individually verified, but the process is subject to human error and becomes inefficient at scale
Solution Approach 1:
The system replaces the mechanical manual data entry process with an automated computational system. Instead of users manually typing and verifying data through a graphical user interface, the system uses file name pattern matching and automated mapping to extract and populate category information, eliminating human error while maintaining reliability
Solution Approach 2:
The system creates a mapping model that copies the structure and rules from manually defined category relationships. This mapping is then applied automatically to categorize documents, replicating the accuracy of manual verification at machine speed without the associated errors
3Productivity
If the system automates categorization by analyzing file names, then processing speed increases for large volumes of documents, but the system requires complex configuration of mapping patterns and character segments
Solution Approach 1:
The system segments file names into distinct character portions, each corresponding to specific category values. By dividing the file name into manageable segments with defined mapping rules, the system makes the automation configuration systematic and manageable, allowing users to define patterns for different portions of file names without overwhelming complexity
Solution Approach 2:
The mapping pattern configuration system is designed to be universal, allowing the same framework to handle different file naming conventions and category types. Once the mapping structure is established, it can be applied to various document types and categorization needs, reducing the perceived complexity through reuse of the same mechanism
Data Source
AI summary
Provided is a software process that can dynamically identify and display a plurality of category values of an electronic file based on a file name assigned to the electronic file. Thus, the software can automatically populate a user interface with details about content within the electronic file based on the file name. In one example, the method may include receiving an electronic computer file having a file name, identifying a subset of characters within the file name which correspond to a data category, mapping a value of the identified subset of characters to a category value in the data category, displaying an identifier of the electronic file on a user interface, and dynamically populating a predefined field within the user interface corresponding to the data category with the mapped category value.