Progressive Profile Inference for Online Matching
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Solution Overview
Problem
Users are reluctant to provide detailed profile information in online matching systems, leading to either poor compatibility results or non-participation, as they may prefer not to share accurate data or refrain from participating altogether.
Innovation Solution
Implementing a progressive profile inference method where users can view other profiles and provide incremental inputs, allowing the system to infer their own profile elements based on annotations and interactions, with the option to verify and modify inferred information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users are required to provide complete profile information upfront, then compatibility estimation accuracy is improved, but user participation rate deteriorates
Solution Approach 1:
The profile information collection process is segmented into multiple stages: initial minimal information collection, incremental information gathering through interactions, and progressive profile completion. Users provide basic information upfront to enable immediate participation, then gradually add more details as they engage with the system, resolving the contradiction between requiring complete information for accuracy and allowing participation with minimal information.
Solution Approach 2:
The system performs preliminary compatibility matching using minimal initial profile information, allowing users to participate and view matches before completing their full profiles. This preliminary action enables immediate user engagement while the system progressively refines compatibility estimates as more profile information becomes available through user interactions and optional profile completion.
2Reliability
If users provide detailed profile information, then compatibility results quality is improved, but user effort and time consumption deteriorates
Solution Approach 1:
The system infers additional profile information automatically from user interactions, preferences, and behavior patterns without requiring explicit user input. Users provide minimal information and the system self-generates the rest by analyzing their matching preferences, viewed profiles, and interaction patterns, thereby maintaining high compatibility result quality while minimizing user time investment.
Solution Approach 2:
The system accepts partial profile information from users and performs compatibility matching with incomplete data, gradually improving results as more information becomes available. Rather than requiring complete information before providing value, the system delivers partial compatibility results immediately and enhances them over time, reducing the perceived effort required from users.
3Measurement precision
If users provide accurate profile information, then matching precision is improved, but user privacy exposure deteriorates
Solution Approach 1:
Profile information is segmented into public and private components. Public information used for matching includes only essential attributes needed for compatibility assessment, while sensitive personal information remains private and is not exposed to other users. The system segments data collection to gather only the minimum necessary information for matching purposes, protecting user privacy while maintaining matching precision.
Solution Approach 2:
The system acts as an intermediary that processes and anonymizes user profile information before using it for matching. Sensitive information is transformed into aggregated or anonymized forms that preserve matching precision without exposing individual user identities or private details, thereby reducing privacy exposure while maintaining accurate matching capabilities.
Data Source
AI summary
Embodiments are directed towards inferring an online matching profile based on progressively receiving a prospect's inputs. Access to other matching profiles is provided to the prospect, and while viewing such profiles of other participants, the prospect may progressively provide inputs, such that the prospect's profile may be inferred. As the prospect continues viewing and progressively providing additional inputs, a number of compatibility metrics presented to the prospect may be increased, as does a degree of compatibility of matches that may be suggested to the prospect. At any time during the viewing and progressive input process, the prospect may be presented with their inferred profile. The prospect may then accept and/or modify various elements within the inferred profile.