Tag-Based User Profiling via ML Session Tracking
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Solution Overview
Problem
The proliferation of webpages and app pages has led to an exponential increase in user inputs, often limiting data processing to independent sessions, which restricts the depth of user characterization for page customizations and tracking, especially since many pages do not require login, thereby missing potentially useful data from prior sessions.
Innovation Solution
A tag processing system distributes unique tag codes to client devices to monitor predefined events, processing input data using machine learning models to identify user profiles, and transmit key-value pairs for session identification, enabling the tracking of user interactions across sessions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If login capabilities are implemented to retrieve user-specific data from prior sessions, then user characterization depth is improved, but user convenience deteriorates due to additional authentication requirements
Solution Approach 1:
The patent introduces tag codes as an intermediary mechanism that enables cross-session user tracking without requiring login. These tags are distributed to client devices and allow the system to retrieve user-specific data from prior sessions anonymously, thus maintaining user convenience while improving user characterization depth through persistent identification across sessions.
2Ease of operation
If independent-session processing is used to maintain user convenience, then ease of operation is improved, but user characterization depth deteriorates due to inability to access prior session data
Solution Approach 1:
The patent implements continuity of useful action by enabling persistent user identification across multiple sessions through tag codes. The system continuously tracks user interactions by maintaining tag data on client devices and retrieving it across sessions, allowing uninterrupted user characterization without requiring repeated authentication, thus preserving both convenience and characterization depth.
3Measurement precision
If tag codes are distributed to enable cross-session tracking, then user characterization depth is improved, but system complexity increases due to additional infrastructure requirements
Solution Approach 1:
The patent uses copying by distributing lightweight tag code copies to client devices. Each client device stores a copy of the tag data locally, enabling cross-session identification without requiring complex centralized storage or processing infrastructure. This approach maintains user characterization depth while minimizing system complexity by leveraging existing client-side capabilities.
Data Source
AI summary
Methods and systems are provided for processing tag-based event communications using machine learning. One or more event communications are received from a user device. The communication(s) include key-value pairs representing an ordered sequence of multiple interaction events of a set of predefined events. Each communication of the one or more event communications includes one generated via execution of tag code integrated with code of an app page or of a webpage. A representation of the ordered sequence is processed using a machine learning model to generate one or more profile estimation results that include an identification of a particular user profile from amongst a set of stored user profile. Profile data is transmitted to a client system that identifies the particular user profile or is from the particular user profile.