Implicit User Response Measurement via Channel Switching and Viewing Duration
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Solution Overview
Problem
Existing mechanisms for determining user response to media content are limited, relying on explicit user feedback which can be inaccurate and require cooperation, and fail to provide detailed insights into individual interest and satisfaction levels.
Innovation Solution
The implementation of implicit mechanisms that analyze user behavior, such as viewing duration, channel switching frequency, and device data, to passively determine user interest, engagement, and satisfaction levels, allowing for personalized content recommendations and advertising.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If explicit user feedback mechanisms are used, then user response can be directly obtained, but the accuracy and reliability of user response data are limited due to user cooperation requirements and potential inaccuracy
Solution Approach 1:
The patent replaces explicit mechanical feedback mechanisms (users manually rating content) with implicit automated measurement mechanisms (system automatically measuring viewing duration, channel switching frequency, and other behavioral metrics). This substitution eliminates the need for user cooperation while providing more accurate and reliable data about actual user engagement and interest levels.
2Loss of information
If explicit rating mechanisms are used, then content providers can obtain user feedback, but the system complexity and user burden increase
Solution Approach 1:
The system performs self-service by automatically collecting and analyzing user behavior data without requiring active user participation. The media playback system autonomously measures viewing duration, tracks channel switching frequency, and generates interest factors without asking users to provide feedback, thereby reducing system complexity from the user perspective while maintaining comprehensive information collection.
3Ease of operation
If implicit measurement mechanisms are used, then user response can be determined without explicit input, but the system requires sophisticated data analysis capabilities
Solution Approach 1:
The patent segments the complex data analysis task into distinct computational steps: (1) measuring basic metrics like viewing duration and channel switching frequency, (2) calculating interest factors by comparing actual viewing duration to content duration, (3) generating relative interest factors by comparing against user's other media consumption patterns. This segmentation makes the sophisticated analysis manageable and systematic.
Data Source
AI summary
Mechanisms are provided for implicitly determining user response to media content. User response may include satisfaction, interest, and engagement levels. User response is determined implicitly by measuring channel switching, channel switching frequency, duration of viewing time, content duration, etc. in a linear or non-linear manner. In one example, the viewing duration evaluated with the media content duration to generate an interest factor. A relative interest factor for the media content is generated by referencing interest factors for the user for other pieces of media content for the user. User responses can be analyzed to determine user attention span, make content recommendations, deliver selected versions of content, customize advertising for a user, etc.