Social Discovery Graphs via Transaction and Location Data
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Solution Overview
Problem
Current social networking services struggle to facilitate meaningful interactions between individuals with similar interests and lifestyles, relying on self-reported preferences that may not accurately reflect actual habits and behaviors, making it difficult to form genuine social connections.
Innovation Solution
A system that combines real-time location data with transaction data to create holistic consumption and lifestyle profiles, allowing users to discover others with similar interests and habits, and providing features for social interactions, gifting, peer-to-peer payments, group buying, and crowdfunding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If self-reported preferences are used to build user profiles, then the system is simple to implement, but the accuracy of social compatibility indicators deteriorates
Solution Approach 1:
The patent introduces transaction data from third-party merchants as an intermediary objective measure to validate and supplement self-reported user preferences. This mediator provides unbiased evidence of actual consumption behavior, resolving the contradiction between implementation simplicity and measurement accuracy by adding an external verification layer without completely replacing the original self-reporting mechanism
Solution Approach 2:
The system implements feedback loops where transaction data continuously updates and refines user profiles. Actual purchase behavior feeds back into the profile construction process, allowing the system to progressively improve accuracy of social compatibility indicators while maintaining the original simple self-reporting interface for users
2Measurement precision
If transaction data is integrated with location data to create holistic profiles, then measurement precision of user characteristics improves, but device complexity increases
Solution Approach 1:
The patent creates a universal profile structure that can accommodate multiple data sources (self-reported preferences, transaction data, location data) within a single integrated framework. This multi-functional profile system resolves the contradiction by providing a unified approach that improves measurement precision without requiring separate complex systems for each data type
Solution Approach 2:
The system employs data integration intermediaries that standardize and harmonize different data formats from multiple sources. These intermediaries manage the complexity of integrating transaction and location data while presenting a simplified unified profile to end users, effectively decoupling the complexity of data integration from the user experience
3Productivity
If real-time data processing is implemented to enable dynamic social discovery, then productivity of social matching improves, but use of energy increases
Solution Approach 1:
The patent implements periodic batch processing of transaction and location data rather than continuous real-time processing. This periodic action maintains productivity of social discovery by regularly updating profiles and matching opportunities while significantly reducing energy consumption compared to continuous real-time processing, resolving the contradiction between speed and energy use
Solution Approach 2:
The system performs preliminary data aggregation and profile updates in advance of user queries. By pre-processing transaction and location data into ready-to-use profile segments, the system enables fast social discovery responses without the need for energy-intensive real-time computation during user interactions
Data Source
AI summary
The disclosed embodiments include methods and systems for providing social discovery service operations. In one embodiment, a system for providing a social discovery service is disclosed. The system may be configured to receive transaction data relating to one or more purchase transactions involving one or more merchants and one or more consumers. The system may also be configured to receive product data identifying one or more products included in the one or more purchase transactions. The system may also receive location data associated with the one or more purchase transactions. Based on the transaction data, location data, and the product data, the system may be configured to generate one or more social discovery graphs. Further, the system may be configured to perform one or more social discovery operations based on the one or more social discovery graphs.