Personalized Broadcast Buffer for Viewer-Content Filtering
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Solution Overview
Problem
Traditional censorship methods in live-streaming apply the same editing to all viewers, failing to provide personalized content filtering based on the viewer-broadcaster relationship level, which can lead to inappropriate content being viewed by unsuitable recipients.
Innovation Solution
A method and system that use machine learning and natural language processing to identify sensitive content and adjust buffer lengths based on viewer-broadcaster relationship levels, allowing for personalized censorship by delaying or removing sensitive content from viewer feeds accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional censorship methods apply the same editing to all viewers, then the censorship process is simple and uniform, but inappropriate content may be viewed by unsuitable recipients
Solution Approach 1:
The patent implements personalized censorship buffers for different viewers based on their relationship level with the broadcaster. Each viewer receives a customized buffer length that reflects their specific relationship with the content creator, allowing appropriate content filtering tailored to individual viewer contexts rather than applying uniform censorship to all
Solution Approach 2:
The censorship system segments viewers into different relationship levels (e.g., close friends, acquaintances, public) and applies different buffer lengths to each segment. This segmentation enables the system to manage complexity by categorizing viewers into discrete groups with predefined censorship parameters
2Adaptability or versatility
If buffer length is adjusted based on viewer-broadcaster relationship level, then personalized content filtering is achieved, but processing time and computational resources increase
Solution Approach 1:
The system pre-determines relationship levels and associates predefined buffer lengths with each relationship category before content is generated. When a viewer accesses content, the system quickly retrieves the appropriate pre-established buffer parameters based on the viewer's relationship level, avoiding real-time complex calculations and reducing processing delays
3Reliability
If sensitive content is censored based on adjusted buffer length, then content appropriateness for each viewer is improved, but information loss occurs for suitable recipients
Solution Approach 1:
The censorship buffer length is locally optimized for each viewer based on their relationship level with the broadcaster. Viewers with closer relationships receive shorter or no buffers, allowing them full access to content, while viewers with distant relationships receive longer buffers that filter sensitive material. This ensures each viewer receives appropriately filtered content without unnecessary information loss
Data Source
AI summary
A method for censoring a broadcast includes sending a notification that viewing content is being recorded by a broadcaster and available for viewing. They method also includes identifying one or more viewers that have accepted the notification and identifying the one or more viewer's viewers' relationship level to the broadcaster. The method also includes generating a buffer for the viewer. The method also includes determining a sensitive content occurrence frequency of the broadcaster and adjusting the buffer length based on the relationship level for the viewer. The method also includes parsing the broadcast of the broadcaster to identify sensitive viewing content, and, in response to a determination that the sensitive viewing content exceeds the viewer's relationship level, censoring the sensitive viewing content based on the adjusted buffer length of a buffered version of the broadcast transmitted to the viewer.