Digital Media Library Matching Algorithm for User Compatibility
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Solution Overview
Problem
Existing matchmaking services, including professional matchmakers and online dating sites, are limited in their ability to accurately match individuals based on shared interests and tastes, often relying on incomplete or exaggerated information, and are constrained by small user networks and limited social connections.
Innovation Solution
A system and method that compares digital media libraries between users, generating a score based on common media files and personal information to identify matches, using a matching algorithm that considers song titles, artist names, album names, and playback frequency, and allows users to specify additional criteria like location and occupation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If professional matchmakers are used to gather and analyze client information, then matching accuracy may improve, but service cost increases significantly
Solution Approach 1:
The patent replaces the mechanical human judgment system of professional matchmakers with an automated computer-based recommendation engine that analyzes user profiles and media library data. This substitution eliminates the need for expensive human services while maintaining or improving matching accuracy through systematic data processing and algorithmic analysis.
Solution Approach 2:
The system enables users to automatically upload and manage their own media library data, which is then processed by the recommendation engine without requiring professional intervention. Users self-generate their profile information and the system automatically performs the matching analysis, reducing dependency on paid services.
2Ease of operation
If online dating sites rely on member-entered information, then service accessibility improves, but information reliability deteriorates due to exaggeration
Solution Approach 1:
Instead of relying on self-reported information that may be exaggerated, the system creates copies of actual media files and their metadata from users' media libraries. These objective copies serve as verifiable evidence of user preferences and consumption patterns, providing reliable data without requiring users to manually describe their tastes.
Solution Approach 2:
The media library data acts as an intermediary between the user and the matching system. Rather than users directly stating their preferences (which may be exaggerated), the system analyzes their actual media consumption records as an impartial mediator, revealing true preferences through objective behavioral data.
3Reliability
If social networking sites limit networks to known contacts, then user privacy is protected, but matching scope is constrained
Solution Approach 1:
The system segments user data into different layers: public profile information for privacy protection and media library metadata for matching purposes. This segmentation allows the system to expand matching scope by analyzing media preferences without exposing sensitive personal information, enabling broader connections while maintaining privacy boundaries.
Solution Approach 2:
The system adds a new dimension to social networking by incorporating media library analysis as a separate matching criterion beyond traditional contact-based networking. This dimensional expansion allows users to discover connections through shared media tastes without requiring prior social contact, broadening the matching scope while maintaining existing privacy structures.
Data Source
AI summary
A system and method matches individuals based on the content of their media libraries. The system has a media content processor that extracts information from a media file, and creates one or more media records. The system further includes a matching engine that compares the media records associated with different people, and determines the similarities between the media libraries of the different people. The matching engine may generate a match score for each pair of media records. The system also includes a presentation engine that provides an indication of the degree of match between the media file of one person and the media files of others.