Automated Content Claim Identification and Mitigation
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Solution Overview
Problem
Content hosts like YouTube face issues with unauthorized content claims, where non-authorized parties claim content, leading to revenue and benefit loss for rightful owners, and existing mechanisms are exploited by unauthorized claimants to usurp legitimate rights.
Innovation Solution
A method involving an identification module that ranks content based on a value policy and identifies unauthorized claims, followed by a mitigation module that addresses these claims, using an apparatus and program product to automate the process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual review processes are used to verify content claims, then accuracy in identifying unauthorized claims is improved, but processing time and operational costs increase significantly
Solution Approach 1:
The patent replaces manual mechanical review processes with automated electronic systems including hash-based content identification, database matching algorithms, and automated claimant verification mechanisms. This substitution maintains high accuracy in identifying unauthorized claims while dramatically reducing processing time and operational costs.
Solution Approach 2:
The patent introduces intermediary technological components such as content hash databases, automated matching systems, and electronic verification intermediaries that facilitate accurate and rapid identification of unauthorized claims without requiring direct human intervention in each case.
2Reliability
If comprehensive claim verification processes are implemented, then revenue protection for authorized claimants is improved, but system complexity and operational overhead increase
Solution Approach 1:
The patent implements preliminary actions by pre-registering authorized claimants and their content hashes in databases before infringement occurs. This allows the system to automatically verify claims in real-time without complex verification processes, maintaining high reliability while simplifying operational complexity.
Solution Approach 2:
The patent uses content hash copying and matching techniques where digital fingerprints of authorized content are replicated and stored in databases. This enables automated comparison and identification of unauthorized uses without requiring complex verification of each individual claim, thus protecting revenue while reducing system complexity.
3Productivity
If automated systems are used to process content claims, then processing speed and efficiency are improved, but accuracy in distinguishing authorized from unauthorized claims deteriorates
Solution Approach 1:
The patent employs sophisticated automated electronic systems including hash-based identification, database matching algorithms, and electronic verification mechanisms that maintain high accuracy in distinguishing authorized from unauthorized claims while achieving rapid processing speeds.
Solution Approach 2:
The patent incorporates feedback mechanisms where the automated system continuously learns from verification outcomes, refining its ability to distinguish authorized from unauthorized claims. This feedback loop maintains high accuracy while preserving processing efficiency through iterative improvement of the automated verification algorithms.
Data Source
AI summary
For mitigating unauthorized content claims, an identification module ranks a plurality of content according to a value policy. The plurality of content is provided through a content host. Each content item of the plurality of content is associated with at least one authorized claimant. The identification module further identifies an unauthorized claim for a content item of the plurality of content by an unauthorized claimant. A mitigation module mitigates the unauthorized claim.