NLP Form Pre-filling via Action Command Context Analysis
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Solution Overview
Problem
Content developers often face challenges in manually linking relevant documents to source documents, leading to missing key links that could enhance usability, due to time constraints or lack of desire to locate appropriate target documents.
Innovation Solution
A method utilizing natural language processing (NLP) to analyze messages for action commands, identify relevant target documents, and automatically pre-fill input fields of a form by determining context similarity between the message and form fields, thereby linking the source document to the appropriate target document.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If content developers manually locate and link target documents to source documents, then link accuracy may be maintained, but time consumption and developer effort increase significantly
Solution Approach 1:
The system enables automatic form selection and population by analyzing action commands in messages, allowing the system to self-complete the task of linking source documents to target documents without requiring manual developer intervention. The NLP-based analysis automatically identifies relevant forms and populates input fields based on message content.
Solution Approach 2:
The patent replaces the manual mechanical process of developers searching for and linking documents with an automated computational system. Natural language processing algorithms analyze message content to automatically identify and link appropriate target documents, substituting human manual work with automated text analysis and form recognition.
2Reliability
If content developers manually complete forms and add hyperlinks, then control over link quality is maintained, but productivity decreases due to repetitive manual tasks
Solution Approach 1:
The system automatically performs form completion and hyperlink addition by analyzing action commands in messages. The NLP-based system self-identifies relevant forms, extracts necessary information, and populates fields without requiring developer intervention, thereby maintaining link quality through automated quality control while dramatically improving productivity.
Solution Approach 2:
The patent introduces an intermediary NLP-based analysis system that acts as a mediator between the message content and the form completion process. This intermediary automatically interprets action commands, identifies relevant forms, and populates fields, serving as a quality-controlled bridge that maintains reliability while enabling high-volume automated processing.
3Productivity
If automatic form population is implemented without NLP analysis, then processing speed increases, but accuracy of form selection and population decreases
Solution Approach 1:
The system performs preliminary NLP analysis of action commands in messages before form selection and population. By pre-analyzing the message content to understand the intended action and extract relevant entities, the system ensures accurate form selection and population while maintaining efficient automated processing, avoiding the need for manual correction.
Solution Approach 2:
The NLP-based analysis provides feedback mechanisms that verify the correctness of form selection and population by comparing extracted information against the original message content. This feedback loop ensures high accuracy in automated form completion while maintaining processing speed through efficient algorithmic validation.
Data Source
AI summary
A technique for pre-filling a computing device form with information associated with an action command found in a message includes receiving a message. Content of the message is analyzed utilizing natural language processing (NLP) to locate an action command within the message. NLP is applied to text in the message that is associated with the action command to determine a context of the action command. A similarity algorithm is applied to the text and one or more input fields of the form to identify one or more matching elements between the text and the input fields of the form. Finally, the input fields of the form are automatically pre-filled with information associated with the matching elements in the message whose similarity exceeds a predetermined threshold.