Primary Location Detection via IP Clustering and Transaction Validation
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Solution Overview
Problem
Current methods for determining primary locations associated with a user, such as home and work, are inefficient and often require direct user queries, lacking accuracy in detection without confirmation.
Innovation Solution
A system that uses IP addresses from login histories and financial transactions to cluster coordinates, selecting clusters based on timestamps to identify primary locations, and verifies these locations through financial transaction descriptions to ensure accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If direct user queries are used to determine primary locations, then user input accuracy is improved, but user experience and system efficiency deteriorate due to frequent queries and confirmations
Solution Approach 1:
The system automatically determines primary locations by analyzing IP address clusters and financial transaction data without requiring user input or confirmation. The location detection service autonomously processes login histories, clusters IP coordinates, identifies primary locations based on timestamp patterns, and validates results through transaction descriptions, enabling the system to serve itself rather than requiring continuous user interaction.
Solution Approach 2:
The patent introduces financial transaction descriptions as an intermediary validation mechanism. Instead of directly querying users for location confirmation, the system uses transaction data (e.g., merchant locations, delivery addresses) as a mediator to verify and refine the detected primary locations, thereby maintaining accuracy without burdening users with direct queries.
2Ease of operation
If IP address clustering is used to determine primary locations, then user privacy is improved by avoiding direct queries, but location detection accuracy may worsen without user confirmation
Solution Approach 1:
The system merges multiple data sources—IP address login histories and financial transaction records—to determine primary locations. By combining these independent data streams, the system cross-validates location information without requiring user input, thereby maintaining both privacy and accuracy. The clustering algorithm processes IP coordinates while transaction data provides additional verification points.
Solution Approach 2:
The system implements a feedback mechanism where financial transaction descriptions are used to validate and refine the initially detected primary locations. The transaction data provides feedback on whether the clustered IP addresses correctly identify actual user locations, allowing the system to adjust and improve accuracy without compromising privacy or requiring direct user confirmation.
3Measurement precision
If multiple data sources are integrated for location determination, then location accuracy is improved, but system complexity worsens
Solution Approach 1:
The patent segments the location determination process into distinct functional modules: IP address clustering module, timestamp analysis module, primary location identification module, and transaction validation module. Each module handles a specific aspect of the process, making the overall complex system manageable through functional decomposition. This segmentation allows the system to integrate multiple data sources while maintaining clear processing boundaries.
Data Source
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AI summary
A method is disclosed. The method includes: obtaining, from a management application, a login history including timestamps and internet protocol (IP) addresses corresponding to logins by a user; obtaining coordinates for the IP addresses; determining clusters for the coordinates based on distances between the coordinates; and determining primary locations for the user based on the clusters and the timestamps.