Group Matching System Using Segmented Profiles
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Solution Overview
Problem
Conventional matching systems are inadequate for connecting groups of users as they primarily focus on individual matching and do not effectively utilize real-time and historical data from various sources to facilitate group interactions based on shared interests and proximity.
Innovation Solution
A system and method for programmatically matching groups using location-sensing devices, which correlates and filters user data from multiple sources like social media, to rank potential matches and enable subsequent interactions, utilizing a learning model to select relevant groups based on proximity and interests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional matching systems use basic location and manual criteria for individual matching, then the system is simple to operate, but it cannot effectively match groups based on shared interests and proximity
Solution Approach 1:
The system segments user data into individual profiles and group profiles separately. Individual profiles contain personal attributes while group profiles aggregate interests and characteristics from multiple members. This segmentation allows the system to handle both individual and group matching independently, resolving the contradiction between adding group matching capability and increasing system complexity.
Solution Approach 2:
The patent adds a new dimension of group-level matching alongside existing individual matching. By creating a separate grouping dimension with aggregated user data, the system can perform group-to-group matching without fundamentally altering the individual matching infrastructure, thus improving versatility while controlling complexity growth.
2Measurement precision
If the system processes data from multiple sources in real-time for group matching, then matching relevance is improved, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-aggregating user data into group profiles and pre-calculating group characteristics before matching is needed. Social media data, interests, and user attributes are consolidated in advance, so when real-time group matching is required, the system only needs to compare pre-processed group profiles rather than raw individual data, significantly reducing processing time while maintaining high matching accuracy.
Solution Approach 2:
The system implements feedback mechanisms where matching results and user interactions are fed back into the profile aggregation process. This allows the system to learn from past matches and improve future group matching accuracy without requiring complete re-processing of all data sources, thus improving precision over time while minimizing additional processing time.
3Adaptability or versatility
If the system aggregates user data from multiple group members, then group matching quality improves, but data privacy and security concerns increase
Solution Approach 1:
The system introduces group profiles as intermediaries between individual users and the matching process. Instead of directly accessing and comparing individual user data from multiple sources, the system aggregates data into anonymized or pseudonymized group profiles that serve as intermediaries. This allows effective group matching while protecting individual privacy, as the matching process operates on group-level aggregated data rather than exposing individual user information.
Data Source
AI summary
Provided herein are systems, methods and computer readable media for programmatically performing group matching and facilitating subsequent interaction. An example apparatus may be configured to receive a request event, the request event comprising at least an indication of user profile associated with the first mobile device and an indication of a current personality profile, access a database, utilizing the indication of the user profile and the indication of the current personality profile, to determine at least a first group with which the user profile is associated, access a second database, utilizing information indicative of the first group to identify a set of one or more candidate groups with which to match the first group, select a second group with which to match the first group, transmit information indicative of the second group, receive an indication of a type of feedback, facilitate an interaction with the second group.