Automated Rating Control Loop for Quality-Based Media Ordering
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Solution Overview
Problem
Existing graphic user interfaces for digital media display lack the ability to dynamically adjust quality indicators based on user responses, fail to automatically weigh early users' inputs more heavily, and do not arrange media objects by quality, leading to inconsistent and unoptimized display ordering.
Innovation Solution
A method and interface that dynamically update digital media object quality indicators based on user inputs, adjusting coefficients for users based on response consistency, and rearrange objects by quality, using an automated closed-loop mechanism to prioritize high-quality content.
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 order is simple to implement, but the high-quality content cannot be prioritized and users cannot consistently identify the best content
Solution Approach 1:
The patent implements a dynamic quality indicator system that continuously updates the quality scores of digital media objects based on real-time user responses. The display order is dynamically rearranged according to these changing quality indicators, transforming the static chronological display into a dynamic quality-based ordering system that adapts as new user feedback arrives
Solution Approach 2:
The system establishes a closed-loop feedback mechanism where user responses to digital media objects are collected, processed into quality indicators, and then used to rearrange the display order. This feedback loop ensures that the display consistently prioritizes high-quality content based on actual user preferences rather than upload timing
2Measurement precision
If all user inputs are weighted equally in quality assessment, then the system is simple to operate, but early users' expert assessments are not sufficiently valued and quality indication is less accurate
Solution Approach 1:
The patent applies local quality by assigning different weights to different users based on their individual characteristics and historical performance. Early users who have demonstrated consistent quality assessment ability are given higher weights, while later users receive lower weights. This localized differentiation optimizes the overall quality indicator accuracy without requiring complex manual intervention
3Extent of automation
If user coefficients are manually adjusted based on response consistency, then the weighting can be optimized, but the system requires manual intervention and is not fully automated
Solution Approach 1:
The system implements self-service by automatically calculating and adjusting user coefficients based on the consistency of their responses with the majority opinion. The algorithm autonomously monitors response patterns, identifies consistent users, and adjusts their weights without manual intervention, maintaining both high automation and reliability through objective mathematical criteria
4Productivity
If the display order is fixed and does not rearrange dynamically, then the system is simple to maintain, but high-quality content cannot be continuously prioritized as quality indicators change
Solution Approach 1:
The patent makes the display order dynamic by automatically rearranging digital media objects based on updated quality indicators. As new user responses arrive and quality scores change, the system dynamically adjusts the display sequence to ensure high-quality content remains prioritized, transforming a static display into an adaptive quality-based ordering system
Data Source
AI summary
A method and a graphic user interface for displaying digital media objects and dynamically calculating their quality indicators. 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 quality indicator of the first digital media object is increased if the response is positive and decreased if the response is negative. The amount of increase or decrease is calculated based on a coefficient value associated with the first user. Subsequent responses to the first digital media object from other users impact the quality indicator of the first digital media object and, also, impact the coefficient value of the first user. Updated coefficient value of the first user is used to calculate impact of subsequent responses of the first user to other digital media objects.