Spatial Correlation for Communication Terminal Association
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Solution Overview
Problem
Existing methods for associating multiple communication terminals with a given user are not always feasible or accurate, especially when users intentionally communicate with different parties using different terminals or utilize different pricing plans and service providers, leading to non-overlapping activity periods.
Innovation Solution
A method that correlates the geographical locations of communication terminals over time to identify spatial correlations, using time series analysis and correlation scores to determine which terminals are likely associated with a given user, regardless of network differences or location measurement techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users intentionally communicate with different parties using different terminals or utilize different pricing plans and service providers, then the activity periods of terminals do not overlap, but existing association methods become infeasible or inaccurate
Solution Approach 1:
Instead of associating terminals based on overlapping activity periods (conventional approach), the patent inverts the approach by associating terminals based on non-overlapping location patterns. The system identifies that terminals belonging to the same user tend to visit the same locations at different times, creating a unique spatial fingerprint that is independent of temporal overlap.
Solution Approach 2:
The patent changes the parameter basis for association from temporal (activity periods) to spatial (location patterns). By computing location-based similarity metrics and spatial correlation scores instead of temporal overlap, the system achieves reliable terminal association even when activity periods do not overlap.
2Area of stationary object
If location indications are obtained from different communication networks using different location measurement techniques, then network coverage is expanded, but data heterogeneity increases
Solution Approach 1:
The patent creates a universal location association framework that works across multiple communication networks and location measurement techniques. The system processes heterogeneous location data (from different networks and techniques) through a unified correlation algorithm, making the association method network-agnostic and technique-agnostic.
Solution Approach 2:
The patent introduces a location correlation analysis system as an intermediary that standardizes and harmonizes heterogeneous location data from different networks and measurement techniques. This intermediary layer computes spatial correlations based on location patterns rather than raw data formats, effectively mediating between diverse data sources and the association outcome.
3Productivity
If traditional association methods based on activity profiles are used, then terminals with overlapping activity periods are associated, but terminals used by the same user with non-overlapping schedules are not identified
Solution Approach 1:
The patent replaces the mechanical/temporal-based association system (activity period overlap) with a spatial-based correlation system. Instead of checking whether activity periods overlap in time, the system computes spatial correlations of location patterns, substituting temporal mechanics with spatial analysis.
Data Source
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AI summary
Methods for associating multiple communication terminals with a given user, based on the geographical locations of the terminals. A target user may be known to own or operate a certain communication terminal (e.g., cellular phone). To identify additional terminals associated with this user, historical location indications are obtained for the known terminal. Each location indication indicates the geographical location of the terminal at a given time. The location indications of the known terminal are correlated with location indications of other terminals. When significant spatial correlation is found between the known terminal and another terminal, the other terminal is assumed likely to be associated with the same target user.