Moderation Task Prioritization via Predictive Success Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing multimedia generation systems face inefficiencies in utilizing human moderators due to insufficient resources and high moderation costs, as they struggle to prioritize tasks effectively, leading to suboptimal video clip quality and quantity under time constraints.
Innovation Solution
A method and system that preprocess moderation tasks to predict success measures, such as likelihood of acceptance and newsworthiness, and prioritize their delivery to human moderators, ensuring that high-priority tasks are addressed first, optimizing moderator resource allocation and improving video clip generation efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If moderation tasks are processed without prioritization, then all tasks are handled equally, but moderator resources are wasted on low-success tasks and productivity decreases
Solution Approach 1:
The system performs preliminary analysis of moderation tasks before they reach human moderators, predicting success measures such as likelihood of acceptance and newsworthiness. This advance preparation allows the system to pre-sort tasks by predicted success, ensuring moderators receive tasks in optimal order without wasting time on low-probability tasks.
Solution Approach 2:
The patent replaces manual task prioritization by moderators with an automated computer-based prediction system. The system uses algorithms to automatically analyze task characteristics, predict success measures, and prioritize task delivery, substituting human judgment with computational analysis to improve efficiency and objectivity.
2Productivity
If more moderation tasks are assigned to increase video clip quantity, then productivity increases, but moderation costs increase due to insufficient human resources
Solution Approach 1:
The system pre-evaluates and prioritizes tasks before moderator review, filtering and sorting tasks by predicted success measures. This preliminary action maximizes the effective utilization of each moderator's time, allowing the system to process more tasks with the same number of moderators by ensuring they only work on high-probability tasks.
Solution Approach 2:
The system changes the parameter of task delivery from unsorted or random assignment to priority-based assignment based on predicted success measures. By transforming the delivery parameter from equal distribution to optimized prioritization, the system increases overall throughput without requiring proportional increases in moderator resources.
3Manufacturing precision
If tasks are prioritized based on multiple success measures, then video clip quality improves, but the complexity of the prioritization system increases
Solution Approach 1:
The prediction system is designed to evaluate multiple success measures simultaneously - including likelihood of acceptance, newsworthiness, and other quality indicators - using a unified prioritization framework. This multi-functional approach allows the system to consider various quality dimensions without requiring separate prioritization mechanisms for each measure, managing complexity while maintaining comprehensive quality assessment.
Data Source
AI summary
A method includes defining multiple moderation tasks, which originate from respective textual articles that are to be automatically converted into respective video clips following moderation by human moderators. The moderation tasks are pre-processed, so as to predict success measures of the corresponding video clips. Delivery of the moderation tasks to the human moderators is prioritized based on the predicted success measures.