IP-Based Location Approximation Using Historical Data Clustering
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Solution Overview
Problem
Existing methods for determining user location on mobile devices are less effective compared to traditional desktop methods, as they often lack precision and rely on unavailable GPS or Wi-Fi positioning systems, leading to user frustration and suboptimal service provision.
Innovation Solution
A computer-implemented method that analyzes historical location data and current IP address data to identify and score potential locations, adjusting scores for clusters to approximate the user's current location, enabling the provision of location-enhanced services even when precise location determination is not possible.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS or Wi-Fi positioning systems are used for mobile device geolocation, then location precision is improved, but availability deteriorates because these systems are not available or operational for large amounts of time or locations
Solution Approach 1:
The patent introduces an intermediary approach by using IP address analysis as a mediator between the mobile device and location services. When GPS and Wi-Fi positioning are unavailable, the system analyzes the device's IP address to derive location information, thereby maintaining service availability without sacrificing the option for higher precision when primary systems are operational
Solution Approach 2:
The system performs preliminary analysis of IP address data to establish baseline location information before primary positioning systems become unavailable. By pre-processing and storing location-related IP data, the system can quickly provide location services during GPS/Wi-Fi outages without requiring real-time computation when the device needs location services
2Reliability
If IP address analysis is used for mobile device geolocation, then system availability is improved, but location precision deteriorates because carrier IPs are not as informative
Solution Approach 1:
The system performs preliminary analysis of historical location data associated with the mobile device before relying on current IP address analysis. By examining past location information and patterns, the system can improve the accuracy of IP-based location estimation, compensating for the inherent imprecision of carrier IP addresses
Solution Approach 2:
The system implements feedback mechanisms by continuously analyzing and updating location information based on historical data patterns. When IP address analysis provides location estimates, the system refines these estimates over time by comparing with historical location information, thereby improving precision while maintaining the availability benefits of IP-based positioning
3Measurement precision
If manual location correction by user is required, then location precision can be improved, but ease of operation deteriorates because it is slow, cumbersome, and undesirable
Solution Approach 1:
The system implements self-service by automatically analyzing and correcting location information using the mobile device's historical location data and IP address information. Instead of requiring manual user intervention, the system autonomously processes location data, applies corrections based on historical patterns, and provides accurate location services without user effort, thereby maintaining precision while dramatically improving ease of operation
Data Source
AI summary
Systems and methods for approximating a user location are provided. For instance, historical location data and internet protocol address data can be analyzed to identify a plurality of locations. A confidence score for each of the plurality of locations can be determined. Two or more locations of the plurality of locations that form a cluster can be identified and the confidence scores for each of the two or more locations that form a cluster can be modified by adjusting each confidence score by a weight associated with the cluster.