Form Autofill Formatting Using Successful Submission Feedback
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Solution Overview
Problem
Autofill tools often misidentify form fields or use incorrect formatting, leading to errors that prevent successful form submission, consuming excessive processing and network resources due to repeated submissions.
Innovation Solution
A device determines the appropriate formatting for a form field based on the content of the electronic document and information from previous successful submissions, modifies the text accordingly, and automatically fills the form field with formatted text.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If autofill tools use predefined form field identifiers to insert user data, then the filling speed is improved, but the accuracy of data insertion deteriorates leading to misidentification of form fields
Solution Approach 1:
The system uses feedback from previous successful form submissions to learn and improve form field identification. By analyzing which form field identifiers led to successful submissions in the past, the system refines its identification accuracy for future autofill operations, resolving the contradiction between speed and accuracy.
Solution Approach 2:
The system performs preliminary analysis of form page content and structure before inserting data. By pre-processing the form page to understand the context and relationships between form fields, the system improves identification accuracy before the actual data insertion occurs, maintaining both speed and accuracy.
2Ease of operation
If autofill tools automatically insert data without formatting verification, then the operation simplicity is improved, but the form submission success rate deteriorates
Solution Approach 1:
The system performs self-verification of data formatting by automatically comparing the data to be inserted against the expected format requirements of each form field. This self-check mechanism ensures formatting correctness without requiring user intervention, maintaining simplicity while improving success rate.
Solution Approach 2:
The system uses feedback from previous successful submissions to learn the correct formatting patterns for different form fields. By applying this learned knowledge to current data insertion operations, the system ensures formatting correctness automatically, improving reliability without complicating the user experience.
3Measurement precision
If repeated form submissions are performed to correct errors, then the data accuracy is improved, but the consumption of processing and network resources worsens
Solution Approach 1:
The system performs preliminary formatting verification and validation before submitting the form. By checking data accuracy and formatting in advance, the system prevents errors that would require repeated submissions, thereby conserving processing and network resources while ensuring data accuracy.
Solution Approach 2:
The system takes preliminary actions to prevent formatting errors and misidentifications before they occur. By proactively verifying data against expected formats and using learned patterns from previous successful submissions, the system avoids the need for corrective repeated submissions, reducing resource consumption.
Data Source
AI summary
In some implementations, a device may identify a form field, of a form, that is to be filled with text. The device may determine a formatting for the text that is to be used for filling the form field. The formatting for the text may be determined based on content that is indicative of the formatting that is to be used for filling the form field, or information relating to at least one previous filling of the form field that is associated with a successful submission of the form. The device may modify the text in accordance with the formatting that is determined to obtain formatted text. The device may cause filling of the form field with the formatted text.