Private Affinity Matching Architecture for Social Profiles
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Solution Overview
Problem
Conventional social networking platforms inhibit self-expression and accuracy in user profiles due to the public nature of affinities, leading to the omission of fringe interests or eccentricities that may cause embarrassment, resulting in less comprehensive representations of users.
Innovation Solution
An architecture that protects private affinities through encryption and access control, allowing for the identification of matching affinities between users and facilitating their revelation only to those with established connections or in close proximity, while enabling anonymous communication and peer-to-peer advertising opportunities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users include all their affinities in public profiles, then the profile becomes more comprehensive and accurate, but users may experience embarrassment or shame from revealing fringe interests or eccentricities
Solution Approach 1:
The patent segments user affinities into public and private categories, allowing users to selectively disclose information. The system divides the profile into visible public sections and hidden private sections, enabling users to include comprehensive affinities while controlling who sees what, thus resolving the contradiction between completeness and embarrassment.
Solution Approach 2:
The patent introduces a matching system as an intermediary that privately compares user affinities without public exposure. The system acts as a mediator that secretly identifies matches between users based on private affinities and facilitates connections without requiring public disclosure, eliminating the shame factor while maintaining information completeness.
2Object-affected harmful factors
If users omit certain affinities to avoid embarrassment, then their self-expression is protected, but the profile becomes less accurate and comprehensive
Solution Approach 1:
By segmenting affinities into public and private categories, users can include all their interests in the profile (maintaining accuracy) while marking sensitive ones as private (protection from embarrassment). The segmentation allows the full profile to exist without public exposure of selected items.
Solution Approach 2:
The matching system serves as an intermediary that privately accesses and compares omitted affinities without public disclosure. It recovers the accuracy lost from omission by secretly utilizing private affinity data to identify genuine matches, allowing users to be comprehensive without embarrassment.
3Object-affected harmful factors
If private affinities are protected from public inspection, then user privacy is enhanced, but the ability to match users based on these affinities is reduced
Solution Approach 1:
The matching system acts as a private intermediary that secretly compares protected affinities without public exposure. It performs the matching function by privately accessing encrypted or hidden affinity data, computing matches behind the scenes, and only revealing results to relevant users, thus maintaining both privacy and matching efficiency.
Solution Approach 2:
The patent replaces public mechanical comparison (visible profile scanning) with private computational matching (backend affinity comparison). The system substitutes transparent manual inspection with automated private algorithms that efficiently compare protected affinities without public exposure, maintaining productivity while enhancing privacy.
4Productivity
If conventional systems require public disclosure of affinities for matching, then matching can be performed, but users are inhibited from self-expression
Solution Approach 1:
The matching system serves as a private intermediary that enables matching capability without requiring public self-expression. It secretly compares affinities and facilitates connections behind the scenes, allowing users to express themselves freely in private while the system performs matching functions independently of public disclosure requirements.
Solution Approach 2:
The patent inverts the conventional approach by not requiring public disclosure for matching. Instead of making affinities public to enable matching, it keeps affinities private and uses the private state as the basis for matching, turning the traditional logic upside down to simultaneously achieve matching capability and self-expression freedom.
Data Source
AI summary
The claimed subject matter relates to an architecture that can leverage private affinities in order to facilitate or enrich relationships between people. In particular, the architecture can receive a profile associated with a user wherein the profile includes a set of private affinities that are cryptographically protected from public inspection. The architecture can decrypt and/or cryptographically compare a private affinity from the profile to an affinity in a disparate profile (associated with a disparate user) in order to identify a matching affinity. Once a matching affinity is identified, a message indicating such can be provided to the user along with a request to publish certain revealed information to the disparate user, possibly based upon a mutual exchange of commensurate information from the disparate user.