Disability-Aware Media Recommendation System
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Solution Overview
Problem
Existing media distribution systems struggle to recommend media content items that are accessible and enjoyable for users with disabilities, as the compatibility of content with a user's disability type is often overlooked.
Innovation Solution
A content recommendation application that identifies users with disabilities and recommends media content items based on the type and severity of the disability, using favorability factors that account for the user's ability to comprehend different types of content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If media content items are recommended based on user consumption history and general interests, then recommendation accuracy for general users is improved, but accessibility for users with disabilities deteriorates
Solution Approach 1:
The patent applies local quality by tailoring recommendation characteristics to match specific disability types. The system determines the user's disability type (visual, hearing, cognitive, etc.) and adjusts recommendation criteria accordingly - for example, prioritizing content with transcripts for hearing impairments or descriptive audio for visual impairments. This localized adaptation resolves the contradiction by making recommendations accessible to disabled users while maintaining accuracy through disability-specific filtering.
Solution Approach 2:
The system changes recommendation parameters based on disability type. Instead of using uniform recommendation criteria, the system modifies parameters such as content accessibility features, format requirements, and compatibility criteria according to the user's specific disability. This parameter adaptation allows the system to maintain recommendation accuracy while removing accessibility barriers for users with disabilities.
2Productivity
If content is recommended based on popularity and trending items, then user engagement is improved, but suitability for users with disabilities deteriorates
Solution Approach 1:
The patent segments the recommendation process into distinct phases: first identifying popular and trending content, then filtering and adapting it based on disability type. This segmentation allows the system to maintain engagement through popularity-based recommendations while ensuring suitability by applying disability-specific filters. The segmented approach resolves the contradiction by handling popularity and accessibility as separate, manageable stages.
Solution Approach 2:
The system introduces an intermediary filtering layer between popular content and final recommendations. This intermediary component evaluates trending items against disability-specific criteria and mediates the selection process. The intermediary ensures that popular content is adapted to be suitable for users with disabilities while still maintaining engagement, resolving the contradiction between popularity-driven engagement and disability-specific suitability.
3Object-affected harmful factors
If the recommendation system considers multiple factors including disability type, then accessibility is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary action by pre-determining disability types and pre-establishing compatibility criteria before the recommendation process. User disability information is collected and stored in advance, and content is pre-tagged with accessibility metadata. This preliminary preparation simplifies the actual recommendation process while maintaining high accessibility, resolving the contradiction between comprehensive accessibility consideration and system complexity.
Data Source
AI summary
Systems and methods are provided for recommending media content to users with disabilities. In response to determining that a user has a disability, a type of the disability is determined. A media content item to recommend to the user is determined, among a plurality of media content items, based on the determined type of disability and a favorability factor of the media content item for the determined type of disability. The favorability factor of the media content item corresponds to an ability of a user with the determined type of disability to comprehend the media content item. An identifier of the determined media content item is generated for presentation.