UID Correlation Across Network Domains Using Event Data
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Solution Overview
Problem
There is a lack of efficient methods to link user identities (UIDs) across different network domains, such as mobile communication and Internet services, without requiring active user input, limiting the ability of service providers to offer personalized services and improve customer support.
Innovation Solution
A method and apparatus that correlate event information from different network domains by comparing user IDs, timestamps, and geographical data to identify associations between UIDs, using a probability-based approach to determine potential links between UIDs from different domains.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users are asked to actively provide correlation information between their UIDs (e.g., during registration), then the accuracy of UID linking is improved, but the extent of automation deteriorates because it requires active user input
Solution Approach 1:
The system performs automatic UID correlation by analyzing event information patterns (timestamps, geographical data, device identifiers) without requiring user action. The network node independently identifies correlations between UIDs from different network domains by processing available event data, making the system self-sufficient and eliminating the need for active user participation in the correlation process
Solution Approach 2:
The patent introduces event information (timestamps, geographical information, device identifiers) as an intermediary that indirectly links UIDs from different network domains. Instead of directly asking users to provide correlations, the system uses these intermediate event attributes as mediators to infer and establish UID associations automatically
2Extent of automation
If no active user input is required for UID correlation, then the extent of automation is improved, but the measurement precision of UID linking deteriorates
Solution Approach 1:
The patent moves from direct UID comparison (one-dimensional) to multi-dimensional analysis by incorporating multiple event attributes including timestamps, geographical information, device identifiers, and event types. This dimensional expansion enables accurate automatic correlation by analyzing patterns across multiple dimensions simultaneously, compensating for the lack of direct user input
Solution Approach 2:
The system uses feedback from multiple event attributes (temporal patterns, geographical consistency, device identifier matching) to iteratively refine and confirm UID correlations. By cross-validating against multiple dimensions of event information, the system builds confidence in automatic correlations without requiring user verification
3Reliability
If traditional registration procedures are used to collect user identities, then the reliability of UID information is improved, but the productivity of service provision deteriorates due to manual processes
Solution Approach 1:
The system performs preliminary automatic UID correlation in advance, continuously analyzing event information from multiple network domains before service requests occur. This pre-computation stores correlation results that can be quickly retrieved and applied during service provision, eliminating the need for real-time manual registration while maintaining reliable UID linkage
Solution Approach 2:
The patent replaces manual registration mechanics with automated information processing. Instead of users manually filling out registration forms, the system automatically extracts and correlates UID information from event logs, timestamps, and network data, substituting mechanical user actions with automated computational processes that are both faster and equally reliable
Data Source
AI summary
Disclosed is a method performed by a network node (300) in a communication network for correlating information of a first network domain (310) with information of a second network domain (320), the second network domain being different from the first network domain. The method comprises receiving (102) event information of a first event that occurred in the first network domain and receiving (104) event information of a second event that occurred in the second network domain, wherein the event information of the first event and the event information of the second event each comprises a user ID, UID; a time stamp, and a geographical information. The method further comprises comparing (106) the event information of the first event with the event information of the second event in order to find a correlation between the event information of the first event and the event information of the second event, the correlation indicating a possible association between the UID of the first event and the UID of the second event.


