Automated Valuation of Third-Party Game Content via Rarity Scoring
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Solution Overview
Problem
Existing video game systems lack a consistent method to value third-party generated content, leading to variability in pricing and inefficiencies in resource utilization.
Innovation Solution
A system and method that analyze third-party generated content files to detect predefined objective properties, calculate a rarity score based on these properties, and assign a rarity level, providing information on the assigned rarity for consistent valuation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual or subjective assessment methods are used to value third-party generated content, then flexibility in evaluation is maintained, but consistency and reliability of valuation deteriorate
Solution Approach 1:
The system enables automatic self-assessment of third-party generated content by analyzing file properties, metadata, and content characteristics without requiring manual human evaluation. The automated valuation system processes content submissions independently, extracting objective properties and calculating rarity scores through predefined algorithms, thereby ensuring consistent and reliable valuation while reducing dependency on subjective human assessment
Solution Approach 2:
The system transforms the valuation process by changing from subjective qualitative assessment to objective quantitative parameter analysis. It extracts specific measurable parameters from content files (such as file properties, metadata attributes, and content characteristics) and uses these parameters to calculate rarity scores and determine valuation, ensuring consistency through standardized parameter-based evaluation
2Measurement precision
If comprehensive analysis of content properties is performed to ensure accurate valuation, then measurement precision improves, but processing time and resource consumption increase
Solution Approach 1:
The valuation system segments the content analysis process into distinct independent stages: file property extraction, metadata analysis, content characteristic detection, rarity score calculation, and final valuation determination. Each segment processes specific aspects of the content separately, allowing for optimized processing of individual properties without requiring comprehensive simultaneous analysis of all content attributes, thereby reducing overall processing time while maintaining measurement precision
Solution Approach 2:
The system performs partial action by focusing analysis on the most significant and relevant content properties rather than exhaustively analyzing every possible attribute. It identifies and prioritizes key valuation-determining properties, applying detailed analysis only to those critical parameters that most influence the final valuation, thus achieving accurate measurement without the time cost of complete comprehensive analysis
3Productivity
If automated valuation systems are implemented to improve efficiency, then productivity increases, but the ability to handle diverse and unique content types may deteriorate
Solution Approach 1:
The valuation system is designed with universal multi-functionality to handle diverse content types including images, videos, audio files, and other media formats. It employs a unified framework that can process different file types through common property extraction and analysis mechanisms, while maintaining the capability to adapt to unique characteristics of each content type through configurable parameters and flexible property detection, thereby achieving both high productivity and broad adaptability
Data Source
AI summary
Described herein is a system and method for valuing third-party generated content within a video game environment. Third-party generated content (e.g., a persona item for a virtual character) for a video game comprising file(s) is received. The file(s) are analyzed to detect more predefined objective property(ies) of the received third-party generated content. A rarity score for the third-party generated content is calculated based, at least in part, upon the detected one or more predefined objective properties and, optionally, a weight assigned to each predefined objective property. A rarity level for the third-party generated content is assigned based, at least in part, on the calculated score. Information regarding the assigned rarity level of the third-party generated content is provided (e.g., to a user of the video game and/or a creator of the third-party generated content).