Tunable Statistical IDs for Advertising Collision Management
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Solution Overview
Problem
Existing methods for user identification in internet advertising environments, particularly for mobile devices, face challenges due to the decline in cookie usage and the inability to uniquely identify browsers, leading to issues with collision and fragmentation of statistical user identification codes.
Innovation Solution
A system and method for generating tunable progressive statistical user identification codes using a database engine, user ID generator, and calibration module, which calculates collision and fragmentation statistics to create a mapping function that produces identification codes with high confidence and accuracy, employing a rotating series of individually-tuned hash functions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If statistical user identification codes are generated using traditional methods, then user identification can be performed, but collisions occur where multiple browsers are assigned the same StatID, reducing identification accuracy
Solution Approach 1:
The patent changes the parameters of the hash function by introducing a progressive counter that modifies the hashing process over time. This allows the system to adjust the statistical properties of StatID generation dynamically, reducing collisions while maintaining identification capability across different browsers and devices.
Solution Approach 2:
The system implements dynamic StatID generation where the hash function evolves over time through the progressive counter mechanism. This dynamic approach allows the identification system to adapt to changing traffic patterns and device types, improving reliability without sacrificing uniqueness.
2Measurement precision
If more identifying characteristics are used to reduce collisions, then StatID uniqueness improves, but fragmentation increases where a single user is assigned multiple different StatIDs
Solution Approach 1:
The patent applies preliminary action by pre-defining a structured set of browser characteristics and a hierarchical hashing approach before StatID generation. This pre-configuration ensures that the same user characteristics consistently map to the same StatID across different sessions, preventing fragmentation while maintaining uniqueness.
Solution Approach 2:
The system segments the user identification process into multiple hierarchical hash functions that process different characteristics at different levels. This segmentation allows the system to maintain uniqueness at each level while ensuring overall consistency for the same user across sessions.
3Reliability
If cookie-based identification is used, then reliable browser identification can be achieved, but compatibility is lost with mobile devices and modern privacy standards that block or disable cookies
Solution Approach 1:
The patent creates a universal StatID system that functions across multiple device types including desktop browsers, mobile devices, and tablets. The identification mechanism uses device-agnostic characteristics that can be collected from any user agent, making the system universally applicable while maintaining reliability through consistent hashing of available characteristics.
Solution Approach 2:
The system uses an intermediary statistical identification layer that sits between the user agent and the advertising system. This intermediary translates various device types and their characteristics into a unified StatID format, enabling cross-device compatibility while preserving identification reliability through the progressive hashing mechanism.
4Measurement precision
If the StatID generation system is made more complex to improve accuracy, then collision reduction improves, but system complexity increases making calibration and maintenance difficult
Solution Approach 1:
The patent implements feedback through automated calibration processes that monitor StatID generation performance and adjust the progressive counter and hash function parameters accordingly. This feedback loop maintains high accuracy while managing complexity by using data-driven adjustments rather than manual configuration.
Solution Approach 2:
The system performs self-calibration using collected browsing data to automatically optimize the StatID generation parameters. This self-service approach reduces the need for external intervention and simplifies maintenance while preserving the accuracy improvements gained from the complex mapping functions.
Data Source
AI summary
A method, system, and computer program product for managing user identification codes in an interne advertising environment. One aspect implements a system including a database engine to store a plurality of signals comprising characteristics and/or values received from a user device. A user ID generator calculates collision statistics and/or fragmentation statistics to form a first mapping function that is in turn used to generate a plurality of identification codes based at least in part a first set of selected signals. A calibration module produces measurements determined from collision quantities and/or fragmentation quantities using the first mapping function, wherein the measurements are determined by comparing the plurality of identification codes to entries in a known ID database. A sequencing module generates updated sequences of mapping functions.