Gamified Matching Engine for Authentic User Profiling
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Solution Overview
Problem
Conventional online dating services often rely on user-entered information, which can be misleading, and fail to effectively match individuals based on more than superficial criteria, leading to unsuccessful connections and misrepresentation.
Innovation Solution
A system and method that uses imagery-based scoring and gamification to derive personal information for matching users, incorporating user interactions and interpretations of outside inputs through a matching engine, which goes beyond traditional attribute matching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional attribute matching based on user-entered information is used, then the matching process is simple and fast, but the accuracy and reliability of matching deteriorates due to potential misrepresentation
Solution Approach 1:
The system performs preliminary actions by having users complete interactive games and activities before the matching process. These games capture user preferences, personality traits, and behavioral patterns in advance, creating a rich dataset that enhances matching accuracy without slowing down the actual matching operation.
Solution Approach 2:
Interactive games and activities serve as intermediaries between users and the matching engine. Instead of directly questioning users about their preferences, the system uses games as a mediator to indirectly capture authentic user behavior and preferences, which then feed into the matching algorithm for more reliable results.
2Ease of operation
If user-entered profile information is used for matching, then the system is easy to operate, but the reliability of information deteriorates due to potential falsehoods
Solution Approach 1:
The system enables self-service by having users naturally reveal their preferences and characteristics through game play rather than through direct questioning. Users inadvertently provide authentic information about themselves through their game choices and behaviors, eliminating the need for them to manually fill out potentially misleading profile sections.
Solution Approach 2:
The system replaces the mechanical system of direct user input (questionnaires, profile forms) with a behavioral observation system. Instead of asking users what they like, the system observes what they actually choose and prefer during game interactions, capturing more genuine preferences without requiring users to consciously report information.
3Loss of time
If superficial criteria are used for matching, then the matching process is quick and simple, but the quality of connections deteriorates
Solution Approach 1:
The system performs preliminary data collection through interactive games before matching occurs. This advance preparation captures deep user preferences and behavioral patterns that would otherwise require extensive questioning during the matching process itself, enabling both quick matching and high connection quality.
Solution Approach 2:
The system transitions from matching based on a single dimension (user-stated preferences) to multiple dimensions by incorporating behavioral data, game choices, response patterns, and interaction styles. This multi-dimensional approach provides richer matching criteria without significantly increasing the time required, as data is collected during natural game play.
Data Source
AI summary
A system and method for deriving personal information to be used in the matching of persons seeking to be matched for social activities is described herein. The system and method provides at least one scoring of information derived from at least one user based on inputted information in response to imagery provided to the user.