Crowd Source Content Editing for Digital Images
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Solution Overview
Problem
The transformation of content from print to electronic form often introduces spelling, formatting, or typographic mistakes due to software or hardware encoding errors, and self-publishing content providers lack professional editing, leading to frustration for consumers and dissatisfaction with electronic content providers.
Innovation Solution
Crowd source content editing leverages a community of content consumers to collaboratively perform editing and proofreading tasks on digital images, using a networked system where users can select and correct errors, with modifications analyzed to determine bona fide corrections and implemented when meeting a modification threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If content is transformed from print to electronic form using automated tools, then distribution speed and reach are improved, but spelling, formatting, and typographic errors increase
Solution Approach 1:
The patent enables content consumers to self-correct errors in electronic content by allowing them to select erroneous text, propose corrections, and submit them for community validation. This self-service approach eliminates the need for manual professional proofreading while improving content accuracy through distributed user intelligence.
Solution Approach 2:
The system implements a feedback mechanism where corrections proposed by users are analyzed against a threshold of agreement from multiple users. When sufficient users agree with a correction, it is automatically applied. This feedback loop continuously improves content quality without requiring traditional editorial review processes.
2Loss of time
If self-publishing providers publish directly in electronic form, then publishing cost and time are reduced, but content quality and professionalism decrease
Solution Approach 1:
Self-publishing providers can publish content immediately without waiting for professional editing or proofreading. The crowd-sourced correction system handles quality improvement automatically as users encounter and correct errors during content consumption, eliminating the time loss associated with traditional publishing workflows.
Solution Approach 2:
The system provides continuous feedback to self-publishing providers about corrections made by the community. This feedback mechanism maintains content quality by systematically identifying and correcting errors while allowing rapid publishing, effectively decoupling publishing speed from quality assurance.
3Manufacturing precision
If professional editing and proofreading are performed, then content quality is improved, but time and cost increase
Solution Approach 1:
Instead of hiring professional editors and proofreaders, the system leverages the intelligence of content consumers who naturally encounter errors during reading. Users self-correct errors as part of their normal content consumption, eliminating the need for dedicated editing personnel and associated costs.
Solution Approach 2:
The patent replaces the mechanical system of human professionals manually reviewing content with an automated crowd-sourced system. Software tools collect, analyze, and implement corrections based on user input, substituting automated processing for manual editorial work and dramatically reducing time and cost.
4Manufacturing precision
If manual proofreading is performed to catch errors, then content accuracy is improved, but productivity and speed decrease
Solution Approach 1:
The patent transitions content accuracy verification from a single-dimension sequential process (one editor reviewing all content) to a multi-dimensional parallel process (many users reviewing different portions simultaneously). This dimensional change enables both high accuracy and high productivity by distributing the proofreading task across the user base.
Solution Approach 2:
Content consumers perform proofreading as part of their natural content consumption process without requiring separate dedicated proofreading resources. This self-service approach maintains content accuracy while preserving processing speed, as users correct errors incidentally during reading rather than requiring systematic manual review.
Data Source
AI summary
Crowd source editing of digital images to reduce errors in a digital images includes receiving a proposed modification to a content portion of a digital image. A determination is made as the whether the occurrence of the proposed modification to the content portions meets a modification threshold. Accordingly, the proposed modification to the content portion of the digital image is adopted when the occurrence of the specific modification meets the modification threshold.