Graph Propagation for Browser Cookie Enrichment
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Solution Overview
Problem
Current systems lack a dedicated data structure to track users' browsing history across multiple websites, web browsers, and computing devices, resulting in incomplete user information and limited personalized content delivery.
Innovation Solution
A network system that generates mapping data structures to relate tracking data from different sources, allowing for the creation of comprehensive user profiles by analyzing relationships between tracking data and predicting the probability of user profile connections across various platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional browser cookies are used for tracking user information, then user identification on single websites is achieved, but user browsing history across multiple websites and devices cannot be tracked completely
Solution Approach 1:
The patent segments the tracking system into multiple components: traditional browser cookies for site-specific tracking, graph database nodes representing users and devices, and graph edges representing relationships. This segmentation allows comprehensive tracking across multiple websites and devices while maintaining manageable complexity through modular architecture.
Solution Approach 2:
The patent adds a graph-based dimension to traditional cookie-based tracking. By creating a graph data structure where nodes represent users/devices and edges represent relationships, the system transitions from flat, single-website tracking to multi-dimensional, cross-platform tracking, enabling complete user profile aggregation.
2Adaptability or versatility
If user information is gathered from multiple sources to create complete user profiles, then personalized content delivery is improved, but data aggregation and processing complexity increases
Solution Approach 1:
The graph database structure serves multiple functions simultaneously: it stores user profiles, tracks device relationships, maintains browsing history, and enables personalized content delivery. This universal data structure handles diverse data types and operations, reducing overall system complexity despite the versatility of personalized content delivery.
Solution Approach 2:
The patent introduces an intermediary graph database layer between raw tracking data and personalized content delivery. This intermediary aggregates and processes information from multiple sources, transforming fragmented data into unified user profiles that can be efficiently used for personalized content while simplifying the overall data aggregation process.
3Reliability
If tracking data is maintained separately for different websites and browsers, then data organization is simple, but user identification across platforms is limited
Solution Approach 1:
The patent merges separate tracking data from different websites and browsers into a unified graph database. By combining isolated cookie data with graph-based user profiles and device relationships, the system achieves accurate cross-platform user identification while preserving the reliability of individual website tracking through the graph structure.
Data Source
AI summary
Systems, methods, and apparatuses are disclosed for generating mapping data structures based on predicted relationships across tracking data obtained from tracking online browsing histories of users to a network of websites.