Automated Content Descriptor Generation for Media Filtering
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Solution Overview
Problem
Users cannot accurately determine the content of multimedia files, as provided metadata may be inaccurate or misleading, and there is no reliable method to filter inappropriate content, especially for children, in a streaming environment.
Innovation Solution
A system that automatically generates content descriptors by analyzing multimedia files using predefined parameters, compares these descriptors to existing file descriptors, and determines a score based on deviations, allowing for reputation ratings of publishers and user profile-based content filtering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If publisher-provided metadata is used to describe multimedia content, then the system is simple and easy to operate, but the accuracy and reliability of content description deteriorates
Solution Approach 1:
The patent introduces an intermediary automated content analysis system that acts as a mediator between the multimedia file and the user. This system analyzes the actual content of multimedia files and generates objective content descriptors, which then serve as a reliable bridge to accurately represent the content without relying solely on potentially misleading publisher-provided metadata.
Solution Approach 2:
The patent implements a feedback mechanism where automated content analysis results are compared against publisher-provided metadata. This feedback loop identifies discrepancies between claimed and actual content characteristics, allowing the system to prioritize accurate automated descriptors over unreliable publisher metadata while maintaining system simplicity.
2Measurement precision
If automated content analysis is implemented to generate accurate content descriptors, then the accuracy of content description improves, but the system complexity and processing time increase
Solution Approach 1:
The patent segments the content analysis process into distinct modular components, each responsible for analyzing specific content characteristics (visual elements, audio elements, text elements). This segmentation allows the complex analysis task to be divided into manageable, independent modules that can be processed separately and combined to form comprehensive content descriptors.
Solution Approach 2:
The patent develops a universal content analysis framework that can handle multiple types of multimedia content (video, audio, text) and analyze various content characteristics through a single integrated system. This multi-functional approach reduces overall system complexity by avoiding the need for separate specialized analysis systems for each content type.
3Reliability
If comprehensive content analysis is performed on all multimedia files, then the reliability of content filtering improves, but the processing time and computational resources increase
Solution Approach 1:
The patent applies partial action by performing automated content analysis selectively rather than on all multimedia files. The system prioritizes analyzing files from publishers with lower reputation scores or files with suspicious metadata, while relying on publisher-provided metadata for files from highly reputable publishers. This partial analysis approach maintains filtering reliability for critical cases while reducing overall processing time.
Solution Approach 2:
The patent implements preliminary action through pre-computation of content descriptors during file upload or ingestion. By performing the computationally intensive content analysis beforehand and storing the results, the system avoids repeated analysis during user requests, significantly reducing processing time while maintaining reliable content filtering capabilities.
4Reliability
If publisher reputation ratings are implemented based on content descriptor accuracy, then the reliability of content selection improves, but the system complexity increases
Solution Approach 1:
The patent implements self-service by allowing the reputation rating system to automatically evaluate and update publisher ratings based on the accuracy of their provided metadata compared to automated content analysis results. The system autonomously computes reputation scores without requiring manual intervention or complex external evaluation processes, thereby improving content selection reliability while keeping the system relatively simple.
Data Source
AI summary
A method is disclosed that includes receiving, from a device of a user, a request to transmit a multimedia file. The method also includes automatically generating a generated content descriptor based on an analysis of the multimedia file using at least one analysis parameter. The method includes determining whether the generated content descriptor satisfies filter criteria of a profile associated with the user. The method further includes rejecting the request to transmit the multimedia file when the generated content descriptor does not satisfy the filter criteria of the profile. The method includes transmitting the multimedia file along with the generated content descriptor when the generated content descriptor satisfies the filter criteria of the profile.