Matching Server Using Non-Self-Identified Data for Relationship Analysis
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Solution Overview
Problem
Existing matching services rely on self-reported data, which may not provide a comprehensive understanding of user traits and preferences, limiting the accuracy of interpersonal relationship matching.
Innovation Solution
A system that uses a matching server to generate match profiles from recorded responses to stimuli, including both self-identified and non-self-identified data such as body language, paralanguage, and biological responses, to create a more comprehensive user profile for compatibility calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If self-identified data is used for matching, then the system is simple to implement and users can explicitly provide information, but the accuracy and comprehensiveness of user trait assessment is limited
Solution Approach 1:
The patent introduces an intermediary system (matching server with automated data collection capabilities) that mediates between users and the matching process. Instead of relying solely on direct user self-reporting, the system uses automated stimuli presentation and response recording to objectively capture user traits, thereby improving assessment accuracy while managing system complexity through automation.
Solution Approach 2:
The patent replaces the manual self-reporting mechanism with an automated psychological assessment system that presents stimuli and records responses. This substitution transforms the data collection process from a subjective, user-driven mechanical process to an objective, system-driven automated process, improving measurement precision.
2Loss of information
If only self-reported data is collected, then the data collection process is straightforward, but the depth of insight into user traits and preferences is insufficient
Solution Approach 1:
The system employs self-service mechanisms where users inadvertently provide comprehensive data through their natural responses to presented stimuli. The automated presentation of stimuli and recording of responses (including body language and paralanguage) allows the system to collect deep behavioral information without requiring users to manually disclose detailed personal traits, thus reducing information loss while maintaining ease of operation.
3Measurement precision
If non-self-identified data such as body language and biological responses is incorporated, then the accuracy of compatibility assessment is improved, but the complexity of the matching system increases
Solution Approach 1:
The patent merges multiple data collection methods (self-reported data, body language analysis, paralanguage detection, and biological response monitoring) into a unified matching system. By combining these diverse data sources through a centralized matching server that processes all inputs together, the system achieves improved compatibility assessment accuracy while managing complexity through integration rather than separate independent systems.
Solution Approach 2:
The matching server is designed as a universal system that handles multiple types of data collection and analysis functions. It can present various stimuli, record different response types (verbal, non-verbal, biological), and process all this information through a single platform, thereby improving assessment accuracy while avoiding the complexity of multiple separate specialized systems.
Data Source
AI summary
An electronic process for presenting interpersonal relationship analysis includes: receiving recorded responses of a plurality of users to selected stimuli, such recorded responses comprising indications of traits and preferences that are not explicitly identified in the recorded response; generating match profile data at least partially from the response; and presenting potential matches to a first user based on a compatibility score generated from correlating match profile data of the plurality of users with the match profile data of the first user.