Short-Form Video Segment Buffering With Retention-Based Prioritization
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Solution Overview
Problem
Existing methods for short-form video streaming are inefficient in managing bandwidth and buffer usage, leading to high wastage and re-buffering due to inadequate segment selection and prioritization, which does not account for user-specific behavior and content-dependent quality.
Innovation Solution
A method for identifying and prioritizing segments for buffering based on user-specific retention rates, segment quality, and network conditions to reduce wastage and improve user experience by selectively pre-buffering segments likely to be viewed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a larger number of segments are buffered to reduce re-buffering and start-up delay, then user quality of experience is improved, but computing resource wastage increases because more segments are discarded when videos are skipped
Solution Approach 1:
The patent applies local quality by differentiating between segments based on their individual characteristics (bitrate, retention rate, quality metrics) rather than treating all segments uniformly. Each segment is evaluated and prioritized based on its specific properties and the user's likely interaction with it, allowing the system to buffer only the most valuable segments while avoiding wastage of resources on segments that are unlikely to be viewed.
Solution Approach 2:
The patent changes the parameters used for segment selection from simple bitrate-based approaches to a multi-parameter evaluation system that includes retention rate, quality metrics, and user behavior patterns. This parameter transformation enables more intelligent segment prioritization that balances quality of experience with resource efficiency by predicting which segments users are most likely to view.
2Device complexity
If segments are pre-buffered based solely on bitrate, then buffering management is simplified, but segment quality perception deteriorates because bitrate does not accurately reflect perceived quality across different content types
Solution Approach 1:
The patent applies local quality by evaluating each segment's actual perceived quality characteristics (retention rate, quality metrics) rather than relying solely on bitrate. This allows the system to accurately assess which segments will provide the best viewing experience, recognizing that different content types have different quality characteristics at the same bitrate.
Solution Approach 2:
The patent incorporates feedback mechanisms by using retention rate data and user behavior patterns to continuously improve segment selection. The system learns from actual user interactions with segments and adjusts future buffering decisions accordingly, creating a feedback loop that refines quality perception accuracy over time.
3Device complexity
If a global retention rate is used for segment selection, then the buffering approach is simplified, but user-specific quality deteriorates because individual user behavior patterns are not accounted for
Solution Approach 1:
The patent applies local quality by transitioning from a global retention rate approach to segment-level evaluation that incorporates user-specific behavior patterns. Each segment is assessed individually with respect to the specific user's viewing habits, allowing the system to adapt to individual preferences and optimize quality for each user's unique consumption patterns.
Solution Approach 2:
The patent introduces dynamics by making the retention rate prediction adaptive and user-specific rather than static and global. The system continuously updates its understanding of individual user behavior patterns, allowing the buffering strategy to dynamically adjust to changing user preferences and viewing habits over time.
Data Source
AI summary
Systems and methods for managing segment buffering in a short-form video application are described. An example method includes identifying a set of recommended content items comprising a first set of segments (which may be “required”) and second set of segments (which may be “optional”). The method includes determining a subset of the optional segments by, for each segment: determining a quality level; determining a predicted retention rate; and selecting the segment for the subset based on a comparison of the predicted retention rate to a retention threshold. The method includes determining a modified set of segments, determining a priority level for each segment of the modified set of segments, and prioritizing the transmission of one or more segments to the client device based on the corresponding priority levels.