Semantic Region Mapping for Social Tie Inference
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Solution Overview
Problem
Existing methods for discovering social ties from cloaked trajectories are inefficient and imprecise due to the imprecision of cloaked location information, which can compromise privacy and make it difficult to analyze mobility patterns effectively.
Innovation Solution
Transforming cloaked regions into semantic regions and mapping them into a hierarchical semantic tree to infer social ties by analyzing relationships between nodes, using techniques such as k-anonymity and reverse geocoding to preserve privacy while accurately determining semantic meanings and similarities between trajectories.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If accurate geographic locations are used to discover social ties, then the precision of social tie inference is improved, but user privacy is compromised due to potential leakage of location data
Solution Approach 1:
The patent introduces semantic regions as an intermediary between accurate geographic locations and social tie inference. Instead of directly using precise location data, the system transforms locations into semantic regions (e.g., POI categories like restaurant, park, school) that preserve mobility pattern information while removing personally identifiable location details, thus enabling social tie discovery without privacy leakage
Solution Approach 2:
The patent changes the parameter representation from precise geographic coordinates to semantic region categories. This parameter transformation converts continuous location data into discrete semantic labels, maintaining the ability to analyze mobility patterns and infer social ties while eliminating the privacy risk associated with exact location information
2Object-affected harmful factors
If spatial cloaking is applied to protect location privacy, then user privacy is protected, but the precision of trajectory analysis deteriorates due to imprecise cloaked locations
Solution Approach 1:
The patent uses semantic regions as a mediator that bridges cloaked locations and meaningful analysis. Even when locations are cloaked to larger regions, the semantic transformation extracts meaningful category information (e.g., knowing a cloaked region contains a restaurant) that preserves mobility pattern insights without requiring precise location data
Solution Approach 2:
The patent transforms the precision requirement from spatial coordinates to semantic categories. Instead of needing precise coordinates for trajectory analysis, the system analyzes patterns in semantic region sequences, which maintains analytical value while working with imprecise cloaked location data
3Object-affected harmful factors
If cloaked trajectories are used to infer social ties, then privacy is preserved, but the efficiency and accuracy of social tie discovery deteriorate due to imprecise location information
Solution Approach 1:
The patent changes the analysis parameter from spatial coordinates to semantic region sequences, enabling efficient processing of cloaked trajectory data. By working with discrete semantic labels rather than continuous coordinates, the system can quickly compute similarities and infer social ties while preserving privacy
Solution Approach 2:
The patent segments trajectories into sequences of semantic regions, breaking down continuous movement data into discrete, analyzable units. This segmentation enables efficient computation of mobility patterns and social tie inference by comparing sequences of semantic categories rather than processing raw coordinate data
Data Source
AI summary
An approach is provided for discovering social ties among users based on cloaked trajectories. In a method, cloaked regions of a first trajectory of a first user and cloaked regions of a second trajectory of a second user are transformed to corresponding semantic regions, respectively, wherein a semantic region is expressed with a semantic meaning of a corresponding cloaked region. The transformed semantic regions are mapped into nodes of a hierarchical semantic tree, wherein each node of the hierarchical semantic tree corresponds to a semantic region. According to relationships between nodes mapped to semantic regions of the first trajectory and node mapped to the semantic regions of the second trajectory, social ties among the first user and the second user can be inferred.