Server System for Multi-Device Entity Association via Location Signatures
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Solution Overview
Problem
Conventional methods struggle to associate multiple electronic devices with a single entity without relying on active user identification, limiting effective retargeting and advertising strategies across devices.
Innovation Solution
A server system that uses location signatures from multiple devices to create geo-polygons and cluster them, allowing association of devices with a single entity based on overlapping location patterns, enabling retargeting and personalized advertising without requiring explicit user identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If active user identification is required to associate multiple electronic devices with a single entity, then association accuracy is improved, but user convenience and ease of operation deteriorate
Solution Approach 1:
The system performs device association automatically without requiring user intervention. The server autonomously collects location signatures from multiple devices, creates geo-polygons, determines intersections, and associates devices with entities based on overlapping location patterns, eliminating the need for users to actively identify themselves across devices.
Solution Approach 2:
The server acts as an intermediary that indirectly associates devices through location pattern analysis. Instead of requiring direct user identification, the server mediates the association process by analyzing geo-polygon intersections and behavioral data to link devices to entities without explicit user input.
2Productivity
If location signature data is collected and processed to create geo-polygons and cluster devices, then advertising retargeting effectiveness is improved, but system complexity and data processing requirements worsen
Solution Approach 1:
The system segments the complex task of device association into distinct processing stages: collecting location signatures, creating individual geo-polygons for each device, determining intersections between geo-polygons, clustering devices based on overlapping patterns, and finally associating devices with entities. This segmentation makes the overall complex process more manageable and systematic.
3Ease of operation
If explicit user identification is not used, then user privacy and ease of operation are improved, but ability to accurately associate devices with entities deteriorates
Solution Approach 1:
The system changes the parameter used for association from explicit user identification to implicit location-based parameters. By using location signatures, geo-polygon intersections, and spatial-temporal patterns as the basis for association, the system maintains accuracy without requiring users to explicitly identify themselves, thus preserving privacy while achieving reliable device-entity linking.
Data Source
AI summary
In a method of associating a single entity with multiple electronic devices, a server accesses user data collected via internet communications with a plurality of electronic devices. Each item of user data includes a location signature and a unique identifier. The server determines an intersection of location between two electronic devices of the plurality of electronic devices based on the user data accessed from the two electronic devices. The user data is accessed from a first of the two electronic devices has a first unique identifier that is different than a second unique identifier of the user data accessed from a second of the two electronic devices. Based on the intersection of location, a single entity is associated with both the first unique identifier and the second unique identifier.