Non-linear Approximation for Unique Visitor Estimation
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Solution Overview
Problem
Existing methods struggle to accurately estimate the number of unique visitors to a network location while protecting user privacy, as direct measurement is often impractical due to factors like multiple visits from different IP addresses and shared user identifiers.
Innovation Solution
A computer-implemented method and system using a non-linear approximation based on estimated user numbers and unique user identifiers within a geographical area, combined with the creation of pseudo-users to estimate unique visitors, allowing for demographic categorization and privacy preservation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If direct measurement methods are used to count unique visitors, then measurement precision is improved, but user privacy is compromised and device complexity increases
Solution Approach 1:
The patent introduces a non-linear approximation function as an intermediary between direct visitor tracking and privacy protection. This mathematical model processes observable data (user identifiers, visit patterns) without requiring direct identification of individual users, thereby maintaining measurement precision while preserving privacy through aggregated statistical analysis rather than individual tracking
Solution Approach 2:
The patent creates a virtual model or copy of the visitor population through non-linear approximation. Instead of measuring actual individual visitors directly, the system generates a statistical representation that captures the essential characteristics of unique visitor counts without exposing real user identities or detailed behavioral patterns
2Object-affected harmful factors
If traditional estimation methods are used, then user privacy is protected, but measurement precision deteriorates due to inability to account for multiple visits and shared identifiers
Solution Approach 1:
The patent transforms the estimation problem by changing the parameters used in calculation. Instead of relying on simple count-based methods, the system incorporates multiple parameters including user identifier distribution patterns, visit frequency distributions, and non-linear relationships between observed identifiers and actual unique visitors. This allows accurate differentiation between multiple visits from same users and shared identifiers across different users
3Measurement precision
If complex tracking systems are implemented to accurately identify unique visitors, then measurement precision is improved, but device complexity and computational resources increase
Solution Approach 1:
The patent extracts only the essential information needed for accurate estimation without implementing complex tracking infrastructure. By focusing on aggregated metrics like total user identifiers observed, visit frequency distributions, and geographic area data, the system achieves precise unique visitor counts without requiring complex user profiling, device fingerprinting, or sophisticated tracking mechanisms
Data Source
AI summary
A system and computer-implemented method for determining an estimated number of unique visitors to a network location from a geographical area. A non-linear approximation is utilized to determine the estimated number of unique visitors to the network location. The non-linear approximation is based on at least the estimated number of users within the geographical area, the estimated number of unique user identifiers within the geographical area, and the number of unique user identifiers from the geographical area that are observed at the network location.