Automatic File Naming from Content Using Neural Networks
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Solution Overview
Problem
Existing methods require manual reading and writing of file names, leading to excessive time costs and inefficiencies in managing file names across multiple files, especially when multiple workers are involved.
Innovation Solution
A method and system utilizing artificial neural networks to automatically create file names based on file contents, including semantic information extraction and adherence to user-defined rules, leveraging large multi-modal and language models to generate file names from image, video, and audio files.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual reading and writing of file names is performed, then file names can be created based on file contents, but time cost becomes excessive and productivity decreases
Solution Approach 1:
The patent replaces the manual mechanical process of reading and writing file names with an automated system using artificial neural networks. The system automatically extracts semantic information from file contents (images, videos, audio) and generates file names according to predefined rules, eliminating the need for manual intervention while maintaining high accuracy.
Solution Approach 2:
The system enables files to serve themselves by automatically generating appropriate file names based on their own contents. The neural network analyzes the semantic information within each file and creates descriptive file names without requiring external human assistance, thus improving productivity significantly.
2Productivity
If automatic file name creation is implemented, then productivity improves, but creating file names according to formal rules becomes technically difficult
Solution Approach 1:
The patent introduces an intermediary component - a prompt generation module - that translates complex file naming rules into simple instructions for the neural network. This intermediary layer receives the desired file naming conventions and converts them into prompts that guide the semantic information extraction and file name generation process, making the system manageable despite its complexity.
Solution Approach 2:
The system segments the file naming process into distinct modules: semantic information extraction from various file types, rule-based prompt generation, and file name creation. This segmentation allows each component to handle specific tasks independently, reducing overall system complexity while maintaining rule compliance.
3Quantity of substance
If multiple workers are involved in file management, then file handling capacity increases, but total time cost increases proportionally
Solution Approach 1:
Each file automatically generates its own name based on its contents, eliminating the need for any worker to spend time on this task. Whether there is one worker or multiple workers, the system processes files autonomously, making the total time cost independent of the number of workers involved.
Solution Approach 2:
The patent replaces the human labor mechanism with an automated neural network system that can process multiple files simultaneously. This substitution eliminates the linear relationship between worker quantity and time cost, allowing parallel processing that reduces total time regardless of organizational structure.
Data Source
AI summary
An automatic file name creation method may include inputting a first file and a first prompt to a first artificial neural network, and creating a first semantic text corresponding to first semantic information of the first file based on an output of the first artificial neural network, receiving second setting information specifying a file name creation rule, creating a second prompt instructing to modify the first semantic text according to the file name creation rule based on the second setting information, inputting the first semantic text and the second prompt to a second artificial neural network, and creating a first file name associated with the first semantic text corresponding to the file name creation rule, based on an output of the second artificial neural network and changing the file name of the first file to the first file name.