Dynamic Media Rating with Self-Recalibrating User Coefficients
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Solution Overview
Problem
Existing graphic user interfaces for digital media display on computing devices lack the ability to dynamically adjust quality indicators based on user responses, fail to account for user consistency in quality assessments, and do not prioritize high-quality content automatically.
Innovation Solution
A method and interface that updates dynamic quality indicators for digital media objects based on user inputs, adjusting coefficients for users based on response consistency across multiple devices, and automatically rearranges content display to prioritize high-quality media.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If digital media objects are displayed in chronological order or estimated pertinence order, then the display structure is simple and easy to implement, but high-quality content cannot be prioritized and users cannot easily identify the best content
Solution Approach 1:
The patent implements dynamic quality indicators that automatically update based on user feedback, transforming the static display order into a dynamic system that adapts to user preferences. The display order changes automatically as users interact with content, allowing high-quality content to rise to prominence without manual intervention while maintaining system simplicity.
Solution Approach 2:
The system incorporates user feedback loops where user interactions with digital media objects directly influence quality indicators. This feedback mechanism enables the system to learn from user behavior and automatically prioritize content that users find valuable, resolving the contradiction between simple display structure and accurate quality assessment.
2Reliability
If user feedback is collected from multiple computing devices, then the quality assessment becomes more reliable and representative, but the system complexity increases due to need for consistency checking and coefficient adjustment
Solution Approach 1:
The system implements self-adjusting coefficients that automatically modify user influence weights based on feedback consistency patterns. Rather than requiring complex external control, the system serves itself by automatically detecting inconsistent feedback and adjusting individual user coefficients, thereby improving reliability without proportionally increasing system complexity.
Solution Approach 2:
The patent dynamically changes user coefficient parameters based on feedback consistency analysis. When users provide feedback that aligns with the majority, their coefficient increases, amplifying their influence. When feedback is inconsistent, the coefficient decreases. This parameter adjustment mechanism enables the system to reliably assess quality while keeping the control logic relatively simple.
3Measurement precision
If user coefficients are dynamically adjusted based on feedback consistency, then the quality assessment becomes more accurate and resistant to manipulation, but the computational overhead and processing time increase
Solution Approach 1:
The system applies coefficient adjustments selectively rather than recalculating all coefficients continuously. It monitors feedback patterns and adjusts coefficients only when significant consistency patterns emerge, reducing unnecessary computational overhead while maintaining assessment precision. This partial action approach balances accuracy with processing efficiency.
4Ease of operation
If the system automatically rearranges digital media objects based on dynamic quality indicators, then users are presented with high-quality content first improving user experience, but the display system becomes more complex requiring continuous monitoring and rearrangement
Solution Approach 1:
The system pre-calculates and stores quality indicators for digital media objects, updating them in the background as user feedback arrives. This preliminary preparation allows the display interface to simply retrieve and show objects in order of their quality indicators without requiring complex real-time rearrangement logic, thereby improving content discovery while managing system complexity.
Data Source
AI summary
A method for displaying digital media objects and dynamically calculating their rating values. A first digital media object is displayed on a first computing device. A first user provides one of predefined inputs corresponding either to a positive or a negative response to the first digital media object. The rating value of the first digital media object is increased if the response is positive and decreased if the response is negative. The numerical change of the rating value is calculated based on a coefficient value associated with the first user. The rating value of the first digital media object and the coefficient value of the first user are dynamically recalculated based on subsequent responses of the first digital media object from other users. The updated coefficient value is used to calculate subsequent numerical changes in the ratings of other digital media objects based on the first user's subsequent responses.