Game Recommendation Engine Mapping Disabilities
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Solution Overview
Problem
Game developers lack the necessary insights and tools to adapt their games for individuals with disabilities, and disabled players struggle to identify accessible games that cater to their specific needs, as existing technologies do not provide effective recommendations for mapping game features to disability aspects.
Innovation Solution
A game recommendation system that utilizes a correlation engine to analyze game and disability attributes, generating recommendations on compatible or accessible game features by establishing correlations between game objects and disability objects, allowing game developers to integrate suitable features into their games and enabling disabled players to find suitable gaming experiences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If games are developed assuming all players are equally capable, then game development is simplified and faster, but accessibility for disabled players deteriorates
Solution Approach 1:
The system performs preliminary analysis of game attributes and disability characteristics before game release, establishing accessibility correlations in advance. This allows developers to identify accessibility issues early in the development process rather than after release, maintaining development efficiency while improving accessibility planning.
Solution Approach 2:
The patent introduces an intermediary recommendation system that acts as a mediator between game developers and disabled players. The system analyzes game attributes, compares them with disability characteristics, and provides recommendations without requiring developers to directly study various disabilities or players to directly test games.
2Adaptability or versatility
If a priori constructed games are customized for disabled persons, then accessibility for specific disabilities is improved, but the ability to provide general game recommendations deteriorates
Solution Approach 1:
The system is designed to serve multiple functions simultaneously: it can provide recommendations for specific disabilities, general accessibility guidance, and even assist game developers in designing accessible games. The correlation engine and recommendation engine work together to handle various query types without requiring separate systems for each function.
Solution Approach 2:
The system changes parameters by analyzing different combinations of game attributes and disability characteristics based on user queries. Rather than maintaining fixed customized games for each disability, the system dynamically adjusts recommendations based on the specific disability type, game category, and attribute correlations established in the database.
3Measurement precision
If game attributes are analyzed in detail for accessibility, then recommendation accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary analysis by pre-establishing correlations between game attributes and disability characteristics during system initialization or offline processing. This allows the correlation engine to quickly retrieve pre-analyzed relationships during actual recommendation queries, reducing real-time processing requirements while maintaining analysis depth.
Solution Approach 2:
The analysis process is segmented into distinct modules: attribute extraction, correlation analysis, and recommendation generation. Each module handles specific aspects of the analysis independently, allowing for optimized processing of different attribute types and enabling parallel computation where applicable.
Data Source
AI summary
A game recommendation engine is presented. Contemplated game recommendation engines are configured to establish correlations among game attributes and attributes of known disabilities. The recommendation engine can further identify or quantify relationships among games and disabilities having the correlated attributes. The relationships can be used to generate and present recommendations to users. For example, a game design can receive recommendations on game features to incorporate into game to be compatible with or accessible to a disabled person, or a disable person can receive recommendations on games that are accessible to or compatible with o them based on their disabilities.