Parental Feedback Video Rating System
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Solution Overview
Problem
The exponential growth of streaming content makes it difficult for parents to manually review and provide accurate ratings, leading to insufficient guidance for monitoring children's media consumption, as existing machine learning systems provide broad ratings that do not account for individual child characteristics.
Innovation Solution
A system that allows parents to provide feedback on videos watched by their children, enhancing content ratings with granularity by considering age, gender, ethnicity, culture, religion, and educational level, and uses this feedback to train machine learning models for personalized content recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If machine learning systems are used to automatically rate streaming media content, then the productivity of content rating increases, but the measurement precision of appropriateness ratings for individual children decreases
Solution Approach 1:
The patent segments the content rating system into multiple components: a machine learning system that provides broad initial ratings, and a parental feedback system that provides granular, child-specific ratings. The system separates general content analysis from individualized appropriessment, allowing each component to specialize in its strength while combining to achieve both efficiency and precision.
Solution Approach 2:
The patent implements a feedback mechanism where parental ratings of content appropriateness for specific children are collected and used to train and improve the machine learning system. This feedback loop allows the system to continuously refine its ratings based on actual parental observations, thereby improving measurement precision over time while maintaining automated productivity.
2Device complexity
If broad machine learning ratings are provided for streaming content, then the device complexity is reduced, but the adaptability to individual child characteristics decreases
Solution Approach 1:
The patent creates a multi-functional rating system that serves multiple purposes: it provides quick automated ratings for general content guidance, collects and processes parental feedback for personalized recommendations, and trains machine learning models for continuous improvement. This universal system handles both broad categorization and individualized adaptation within a single platform.
Solution Approach 2:
The patent implements a dynamic rating system where content ratings evolve from static broad categories to adaptive personalized recommendations. The system dynamically adjusts ratings based on accumulated parental feedback, allowing the same content to have different appropriateness levels for different children based on their individual characteristics and parental observations.
3Measurement precision
If manual parental review of all streaming content is performed, then the measurement precision of appropriateness ratings increases, but the loss of time for parents increases
Solution Approach 1:
The patent applies preliminary action by having the machine learning system generate initial content ratings and recommendations before parental review. This pre-filtering and pre-rating process eliminates the need for parents to manually review all content, reducing their time investment while maintaining the option for them to provide feedback on specific items that matter most to their children.
Solution Approach 2:
The patent implements partial action by allowing parents to selectively review and provide feedback on only a subset of content rather than requiring complete manual review of all streaming material. The system accepts partial parental input on key items and uses this to infer and rate other content, reducing the time burden while still achieving sufficient precision through targeted parental involvement.
Data Source
AI summary
Systems and methods for rating videos based on parental feedback axe presented. In an aspect, a method is provided that includes providing supervisory users respectively having a supervisory role over other users access to watch histories of respective ones of the other users and receiving feedback from the supervisory users regarding appropriateness of a video for the other users, respectively. The method further includes determining an age rating for the media item based on an average age of the other users that the feedback indicates the video is appropriate for, and recommending the video to a user for watching based on the user having an age that satisfies the age rating.