IP Geolocation via Spatial Clustering of User Activity Data
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Solution Overview
Problem
Current methods fail to accurately determine a user's geographic location from an Internet Protocol (IP) address, as multiple users in different locations can share the same IP address, making it difficult for search engines and advertisement providers to tailor search results and digital ads effectively based on user location.
Innovation Solution
Systems and methods are developed to associate a geographic location with an IP address by processing user activity data from registered users, browser cookies, and search queries, creating spatial clusters, and determining accuracy scores to accurately pinpoint the location associated with an IP address.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If IP addresses are shared by multiple users, then network resource utilization is improved, but the ability to determine user location deteriorates
Solution Approach 1:
The patent segments the problem of location determination by creating spatial clusters from multiple data sources (user activity data, browser cookies, search queries) rather than relying on a single IP address. This segmentation allows the system to overcome the limitation of shared IP addresses by dividing the determination process into multiple independent data collection channels that can be aggregated to improve location accuracy.
Solution Approach 2:
The patent introduces intermediary elements (spatial clusters, accuracy scores, and multiple data sources) that mediate between the IP address and the final location determination. These intermediaries allow the system to handle the ambiguity of shared IP addresses by using additional contextual information from user activity, cookies, and search patterns to bridge the gap between IP address and actual user location.
2Measurement precision
If multiple data sources are processed to determine location, then location accuracy is improved, but system complexity increases
Solution Approach 1:
The patent merges multiple data sources (user activity data, browser cookies, search queries) into a unified spatial cluster model. By combining these diverse data types into a single integrated framework, the system achieves improved location accuracy without proportionally increasing complexity, as the merging process creates synergistic effects where the combined data sources reinforce each other.
Solution Approach 2:
The patent changes parameters by introducing accuracy scores that quantify the reliability of location determinations from different data sources. This parameter transformation allows the system to handle complexity systematically by assigning weights and confidence levels to different data sources, enabling automated decision-making that reduces the perceived complexity of processing multiple inputs.
3Measurement precision
If spatial clusters are created from user data, then location association accuracy is improved, but data processing requirements increase
Solution Approach 1:
The patent applies preliminary action by pre-processing and organizing user data into spatial clusters before actual location determination is needed. User activity data, browser cookies, and search queries are aggregated and structured in advance, creating ready-to-use spatial clusters that can be quickly queried when location information is needed, thereby reducing real-time data processing requirements.
Solution Approach 2:
The patent uses copying by creating spatial cluster models that represent geographic locations without requiring continuous access to raw user data. Once spatial clusters are established from user activity patterns, these cluster representations can be copied and reused for multiple location determination queries, significantly reducing the volume of data that needs to be processed for each individual location request.
Data Source
AI summary
The present application is directed to systems and methods for associating a geographic location with an IP address. Generally, an IP address from which each of a plurality of users accesses a network is recorded. A geo tag is associated with each of the plurality of users and a subset of the plurality of users is identified, the subset including users associated with a first IP address. The subset of the plurality of users is clustered into a spatial cluster including users associated with geo tags located with a defined distance of a geo tag of at least one other user of the cluster. A geographic location associated with a geographic center of the cluster is then associated with the first IP address.