Dynamic Video Rebroadcast Scheduling via Viewer Request Feedback
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Viewers face challenges in catching up on missed episodes of television series without waiting for DVD releases or re-broadcasts, and existing technologies do not effectively leverage viewer behavior to dynamically schedule rebroadcasts or set advertisement rates based on popularity.
Innovation Solution
A method to determine the popularity of previously broadcast videos by analyzing rebroadcast requests and dynamically schedule them during peak popularity times, while adjusting advertisement rates accordingly, using a digital video recorder (DVR) system that collects viewing behavior data and interacts with a content provider to manage episode dependencies and user preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional fixed scheduling of rebroadcasts is used, then content providers can maintain regular programming, but viewers cannot access missed episodes in a timely manner and advertisement revenue is not optimized based on actual demand
Solution Approach 1:
The patent implements dynamic rebroadcast scheduling where the scheduling system transitions from fixed, predetermined timetables to flexible, real-time scheduling based on actual viewer requests. The system continuously monitors request patterns and automatically adjusts rebroadcast timing, allowing viewers to access missed episodes when they actually want to watch them rather than waiting for predetermined slots.
Solution Approach 2:
The system incorporates feedback mechanisms by tracking and analyzing viewer requests for rebroadcasts. This feedback loop allows the scheduling system to learn from actual viewer behavior patterns and continuously optimize rebroadcast timing to match viewer demand, thereby improving access speed without requiring complex manual intervention.
2Productivity
If advertisement rates are fixed regardless of content popularity, then pricing is simple, but content providers cannot maximize revenue from high-demand episodes
Solution Approach 1:
The patent implements a feedback-driven pricing mechanism where advertisement rates are dynamically adjusted based on measured content popularity. The system continuously monitors viewer requests, watches, and engagement metrics, then uses this feedback to automatically adjust advertisement pricing for individual episodes, allowing content providers to capture maximum revenue from high-demand content while maintaining simplicity through automated measurement and adjustment.
Solution Approach 2:
The system changes the advertisement rate parameter based on measured popularity metrics. Instead of fixed pricing, the advertisement rate becomes a dynamic parameter that adjusts according to viewer demand, request volume, and engagement data, enabling revenue optimization while the automated measurement system handles the complexity of tracking popularity.
3Loss of information
If manual tracking of viewer behavior is used, then data collection is simple, but the system cannot effectively analyze patterns to optimize scheduling and pricing
Solution Approach 1:
The patent implements comprehensive feedback collection where the system automatically tracks viewer requests, watches, and engagement patterns. This feedback mechanism captures detailed viewing behavior data without manual intervention, then feeds this information back into the scheduling and pricing algorithms to continuously optimize rebroadcast timing and advertisement rates based on actual viewer preferences and patterns.
Solution Approach 2:
The system introduces an intermediary automated data analysis layer that sits between raw viewer behavior data and the scheduling/pricing decisions. This intermediary component automatically processes, analyzes, and translates viewing patterns into actionable scheduling and pricing adjustments, reducing the need for manual tracking while effectively utilizing the collected data to optimize system performance.
Data Source
AI summary
Television viewers want to watch previously broadcast videos for a number of reasons. For example, a viewer may have missed one or more episodes of his or her favorite series. As another example, a viewer may have mistaken the broadcast date of a show. Functionality can be implemented in a video recording device to submit rebroadcast requests for previously broadcast videos to a content provider. The content provider can use the rebroadcast requests to determine popularity of the previously broadcast video and dynamically schedule rebroadcasts of the most popular videos. The rebroadcast requests represent intended viewership of the video and can be leveraged by the content provider when assigning advertisement rates for the rebroadcast.