Personalized Video Channel Generation via Viewer Behavior Monitoring
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Solution Overview
Problem
Media consumers face inefficiencies in channel switching and content navigation due to predictable viewing behaviors, as they often need to manually switch between channels or navigate through program guides to find desired content, which can be repetitive and disrupt the viewing experience.
Innovation Solution
A system that generates a personalized video channel by monitoring and detecting viewer behavior and available media content sources, automatically populating the channel with related or recommended content during designated viewing times, allowing for seamless content presentation without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual channel switching and navigation through program guides is used, then users can find desired content, but the process becomes repetitive and disrupts the viewing experience
Solution Approach 1:
The system performs preliminary actions by automatically monitoring viewer behavior during sampling periods and pre-generating personalized video channels with predicted content before the viewer needs it. This eliminates the need for manual channel switching at the moment of viewing, as the desired content is already prepared and immediately available.
Solution Approach 2:
The system enables self-service by automatically detecting viewer behavior patterns and media content sources, then autonomously generating and updating personalized video channels without requiring manual user intervention. The system serves itself by continuously learning from viewing data and adjusting content recommendations automatically.
2Adaptability or versatility
If periodic pop-up messages with content recommendations are displayed, then users receive personalized recommendations, but users must navigate away from current content and remember the message
Solution Approach 1:
The system merges the recommendation function with the video channel itself by integrating recommended content directly into the personalized video channel stream. Instead of separate pop-up messages, the recommendations become part of the continuous video content flow, allowing users to access recommended content without leaving their current viewing context.
Solution Approach 2:
The personalized video channel acts as an intermediary between the recommendation system and the user. It translates algorithmic recommendations into a natural video format that seamlessly integrates with the user's viewing experience, eliminating the need for users to interact with separate recommendation interfaces or remember discrete messages.
3Adaptability or versatility
If a personalized video channel is generated using monitored viewing behavior, then content selection aligns with viewer preferences, but the system requires automatic monitoring and detection mechanisms
Solution Approach 1:
The system achieves universality by designing a multi-functional platform that simultaneously performs behavior monitoring, content source detection, personalized channel generation, and automatic content population. This integrated approach consolidates multiple functions into a single system architecture, managing complexity through functional integration rather than separate components.
Data Source
AI summary
Systems and methods are provided to generate a personalized video channel for a viewer. Selected parameters of the viewer's viewing behavior with respect to one or more media devices that are associated with the viewer are automatically monitored and detected during one or more sampling periods. Media content sources that are available to the viewer on the one or more media devices are automatically detected. A personalized video channel is then generated for the viewer using at least the monitoring parameters and the detected media content sources. During a viewing session on one of the media devices, the generated personalized video channel is displayed.