Merchant Location Determination via Signal-Transaction Correlation
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Solution Overview
Problem
Current systems lack the ability to accurately determine detailed locations of merchant entities based on correlations between transaction records and signal records, which limits their effectiveness in real-time services such as fraud prevention and targeted advertising.
Innovation Solution
A system that correlates discrete transaction records with signal records captured by consumers' communication devices, using a correlation engine to generate average score ranges and zone maps, allowing for the identification of merchant locations as unique ranges within specific zones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional address-based location data from transaction records is used, then the system is simple to operate, but the location precision is insufficient for detailed merchant location identification
Solution Approach 1:
The patent combines transaction records from payment networks with signal records from communication devices to create a hybrid location determination system. This merging of data sources enables precise location identification by correlating transaction events with geographic signal data, resolving the contradiction between simple operation and high precision through integrated multi-source data processing
Solution Approach 2:
The patent introduces a correlation engine as an intermediary component that processes and correlates transaction records with signal records. This intermediary system bridges the gap between simple transaction data and complex location analysis, providing automated correlation processing that maintains ease of operation while achieving detailed location precision through systematic data matching
2Productivity
If real-time location determination is implemented using signal records, then the service responsiveness is improved, but the data processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary correlation processing by pre-establishing relationships between transaction records and signal records before real-time services are needed. This advance preparation creates a correlated dataset that can be quickly queried during real-time operations, reducing processing time while maintaining high service responsiveness through pre-computed location information
Solution Approach 2:
The patent implements dynamic location range generation that adapts to different service requirements. The system can adjust the level of detail and processing intensity based on real-time needs, providing fast approximate locations when speed is critical and more precise locations when accuracy is prioritized, thereby balancing processing time against service responsiveness
3Measurement precision
If detailed location ranges are generated for all merchants, then the location accuracy is improved, but the data storage requirements and system complexity increase
Solution Approach 1:
The patent generates location ranges with varying levels of detail based on local requirements and merchant characteristics. Rather than uniformly storing high-detail location data for all merchants, the system applies detailed location ranges only where needed for specific services or merchant types, reducing overall data storage requirements while maintaining high location accuracy for priority cases
Solution Approach 2:
The patent implements partial location determination by generating detailed location ranges for a subset of merchants or transactions rather than all. This selective approach provides sufficient location accuracy for critical applications while avoiding the storage overhead of comprehensive detailed location data for every merchant, achieving the right balance through targeted precision
Data Source
AI summary
Exemplary embodiments of systems and methods are provided for determining detailed locations of entities. One exemplary method includes receiving at least one signal record for a communication device associated with a user. The at least one signal record includes multiple signal strengths, a temporal indicator, and an identifier unique to the communication device. The exemplary method further includes accessing multiple discrete event records associated with the entity, correlating one of the multiple discrete event records to the at least one signal record based on the temporal indicator included in the at least one signal record, and generating a location range associated with the entity, based on the signal strengths included in the at least one signal record, whereby a location of the entity, distinct from one or more other entities, is indicated by the location range.