Media Evaluation System Using Phase-Based Voting Scores
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Solution Overview
Problem
There is a lack of a systematic and logical method to evaluate and award high-quality user-generated media files on media sharing websites, leading to disparity in quality and popularity among shared media.
Innovation Solution
A method and system that involves a contest/festival structure where media files are evaluated through four phases based on voting scores calculated from user views, votes, percentage of video viewed, comments, social distribution, and recommendations, promoting the best performing files through multiple phases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If user-generated media files are shared freely on media websites, then the quantity and diversity of media content increases, but the quality and consistency of media files deteriorate due to lack of systematic evaluation
Solution Approach 1:
The patent implements a feedback mechanism where user votes, views, and interactions are systematically collected and used to evaluate media files. The evaluation system processes feedback from multiple users across different phases, generating scores that determine promotion or elimination of media files, thereby maintaining quality standards while allowing quantity to grow
Solution Approach 2:
The system enables users to self-evaluate media files through voting and interaction mechanisms. Users automatically contribute to the evaluation process by viewing, voting, and engaging with media files, creating a decentralized quality assessment system that scales with the quantity of user-generated content
2Manufacturing precision
If a systematic evaluation method with multiple phases is implemented, then the quality and recognition of high-quality media files improve, but the complexity of the system increases
Solution Approach 1:
The evaluation system is divided into multiple distinct phases (first phase, second phase, third phase, finals) where media files are progressively evaluated and promoted. Each phase has specific evaluation criteria and outcomes, breaking down the complex evaluation process into manageable segments that collectively achieve high-quality assessment
Solution Approach 2:
The system dynamically adjusts evaluation criteria and processes based on the phase and performance of media files. The evaluation mechanism adapts to different stages of competition, with promotion decisions based on relative performance within each phase, allowing the system to maintain accuracy while managing complexity through dynamic rather than static rules
3Loss of information
If media files are promoted through multiple phases based on voting scores, then the visibility and recognition of high-quality content increase, but the time required for evaluation and promotion extends
Solution Approach 1:
The evaluation process operates in periodic phases with defined start and end points. Each phase evaluates a subset of media files and promotes winners to the next phase, creating a structured timeline that balances thorough evaluation with timely recognition. The periodic structure prevents indefinite evaluation while ensuring comprehensive assessment
Solution Approach 2:
The system conducts preliminary evaluations in early phases to identify and promote only the most promising media files to subsequent phases. This preliminary filtering action reduces the number of files requiring full evaluation in later phases, thereby reducing overall evaluation time while maintaining visibility for high-quality content that progresses through the phases
Data Source
AI summary
A method and system for evaluating and sharing user-generated media files have been disclosed. The method and system is embodied in a contest/festival that entices visitors to return to the site to vote on their favorite videos by providing a plurality of phases in which the best performing media files are promoted based on voting scores. According to one embodiment, a computer implemented method comprises generating scores for each media file in four phases and calculating the total score for each of the four phases. The scores are calculated based on the number of views and votes from users for each media file. The votes are generated using questions, percentage of video viewed, comments, social distribution, and recommendations.