Multi-screen Network Teaching Video Priority Ranking
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Solution Overview
Problem
Existing network teaching methods fail to accurately and automatically identify the importance levels of multiple video sources, leading to reduced user experience due to the inability to prioritize content effectively across multiple terminal display devices.
Innovation Solution
A multi-screen interactive network teaching method that analyzes video sources using a customized grayscale shadow comparison method to determine action frequencies, ranks importance levels, and assigns corresponding priorities to terminal display devices, ensuring that high-priority content is displayed on the most appropriate devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple terminal display devices are used to display multiple network teaching video sources, then the teaching scenario mapping is expanded and users can access more content, but it becomes impossible to determine the importance levels of the video sources, requiring users to simultaneously watch all devices to identify important content, which reduces user experience and creates inconvenience
Solution Approach 1:
The system performs preliminary analysis of video sources to determine importance levels before user viewing. By pre-calculating action frequencies and importance levels of multiple video sources, the system automatically assigns priority rankings, eliminating the need for users to manually evaluate and switch between multiple devices to find important content.
Solution Approach 2:
The patent replaces the manual mechanical process of users switching between devices and evaluating content importance with an automated electronic analysis system. The system uses algorithms to analyze video content, calculate action frequencies, and automatically determine importance levels, substituting human cognitive effort with automated computational processes.
2Measurement precision
If preset importance level data and division levels of scenarios are used to identify importance levels of video sources, then conditional identification of importance levels is achieved, but intelligent identification of the importance level of all videos cannot be realized
Solution Approach 1:
The system enables video sources to self-evaluate their own importance levels through automated analysis. Each video source is analyzed independently to calculate its action frequency and determine its importance level without requiring external manual intervention or preset category assignments, allowing the system to intelligently adapt to any video content regardless of predefined categories.
Solution Approach 2:
The patent introduces dynamic parameter calculation based on action frequencies extracted from video content analysis. Instead of relying on static preset importance levels, the system calculates importance levels in real-time based on measurable parameters such as action frequency, enabling intelligent adaptation to diverse video sources without requiring pre-defined categories or manual configuration.
Data Source
AI summary
The present disclosure relates to a multi-screen interactive network teaching method and apparatus, an electronic device and a storage medium. The method includes: receiving signals of a plurality of network teaching video sources; analyzing the plurality of network teaching video sources according to a preset analysis algorithm; determining action frequencies of the plurality of network teaching video sources according to analysis results; performing importance level ranking on the network teaching video sources according to the action frequencies of the plurality of network teaching video sources; acquiring entries of correspondence relationships between preset priorities of a plurality of associated terminal display devices and importance level ranks of the video sources, and according to the entries of correspondence relationships, respectively displaying each of the network teaching video sources via a terminal display device with a priority corresponding to the importance level rank of the network teaching video source.