Automated Machine-Readable Link Selection for Documents
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Solution Overview
Problem
The manual selection of machine-readable links, such as barcodes or digital watermarks, for documents is cumbersome and inhibits automated workflows, as it requires manual determination of the appropriate type based on document characteristics.
Innovation Solution
An automated method to determine the appropriate type of machine-readable link (overt or covert) for a document based on its type and characteristics, using a computing device to select and embed the link in the document, ensuring the link meets specific evaluation metrics for optimal readability and accessibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual selection of machine-readable link type is used, then the appropriateness of link type can be determined, but the process becomes cumbersome and workflow efficiency deteriorates
Solution Approach 1:
The system automatically determines the appropriate machine-readable link type by analyzing document characteristics themselves, without requiring manual intervention. The computing device evaluates document properties and autonomously selects the suitable link type, making the system self-sufficient in the selection process.
Solution Approach 2:
The system changes the selection criterion from manual user choice to automated analysis of document parameters and characteristics. By evaluating document properties such as content type, structure, and metadata, the system dynamically determines the appropriate link type based on objective parameters rather than subjective manual judgment.
2Productivity
If automated determination of machine-readable link type is implemented, then workflow efficiency is improved, but the complexity of the system increases
Solution Approach 1:
The computing device performs multiple functions: it analyzes document characteristics, determines the appropriate machine-readable link type, and embeds the link into the document. This multi-functional approach consolidates what could be separate complex systems into a single integrated solution, managing complexity through functional consolidation.
Solution Approach 2:
The system replaces manual mechanical selection processes with automated computational analysis. Instead of human users manually evaluating and selecting link types, the computing device uses algorithmic analysis of document characteristics to automatically determine the appropriate link type, substituting mechanical/manual operations with computational processes.
3Measurement precision
If manual determination of machine-readable link type is required, then evaluation metrics can be carefully considered, but time consumption increases
Solution Approach 1:
The system performs preliminary analysis of document characteristics before the actual link embedding process. By pre-evaluating document properties and determining the appropriate link type in advance, the system prepares the selection criteria and metrics assessment beforehand, eliminating the need for time-consuming manual evaluation during the workflow execution.
Solution Approach 2:
The system uses feedback from document characteristic analysis to automatically adjust and determine the appropriate link type. The computing device continuously evaluates document properties and uses this feedback information to make informed decisions about link type selection, replacing manual metric assessment with automated feedback-driven determination.
Data Source
AI summary
Examples disclosed herein relate to selection of machine-readable link type. Examples include acquisition of an electronic document, selection of a machine-readable link type for evaluation, and a decision of whether at least one characteristic of the document satisfies at least one evaluation metric for use of the selected type of machine-readable link.