Personalized Location Tags for Contextual Privacy
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing location-based services often provide either too much or too little information, as they rely on coarse geographical coordinates, which can be invasive and lack context, failing to convey meaningful user location details without compromising privacy.
Innovation Solution
The implementation of personalized and contextual location tags, where a matching engine analyzes user data to configure geotags with specific locations, radii, and names, allowing users to control access and infer locations based on past behavior, thereby providing relevant information without revealing precise coordinates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If coarse geographical coordinates are used to represent user location, then location information can be shared without revealing precise coordinates, but the location information becomes too generic to convey meaningful context
Solution Approach 1:
The patent applies local quality by creating personalized location tags that are specific to each user's context. Instead of using uniform coarse coordinates for everyone, the system generates location tags tailored to individual users based on their historical data, preferences, and behavior patterns. This allows the same general location to be represented differently for different users, providing meaningful context while maintaining privacy.
Solution Approach 2:
The system creates a virtual copy of the user's location information in the form of personalized location tags. These tags are derived from and represent the actual location data but are transformed into contextualized representations that convey meaning without revealing precise coordinates. The location tags serve as a copy that preserves essential information while filtering out sensitive details.
2Measurement precision
If precise location coordinates are published to provide accurate location information, then location accuracy is improved, but user privacy is compromised and information becomes overly invasive
Solution Approach 1:
The system extracts the essential location information from precise coordinates and separates it from the sensitive spatial data. By taking out the meaningful contextual information and presenting it through personalized location tags, the system maintains location accuracy for the user's needs while removing the invasive precise coordinate data from the shared information.
Solution Approach 2:
The patent changes the parameters of location representation by transforming precise coordinates into personalized location tags with different characteristics. These tags incorporate user-specific parameters such as historical visit patterns, preferred locations, and contextual information, thereby changing the nature of the data from raw spatial coordinates to meaningful contextual representations.
3Device complexity
If multiple users are represented by the same coarse location, then location sharing is simplified, but the location information fails to convey meaningful details about individual users
Solution Approach 1:
The system segments the location information by creating separate personalized location tags for each user. Instead of using a single coarse location for multiple users, the system divides the location representation into user-specific tags that capture individual context. This segmentation maintains simplicity in the overall system while adding meaningful details for each user.
Solution Approach 2:
The location tags are dynamic and adapt to each user's behavior patterns and preferences. The system continuously learns from user interactions and updates the location tags to better reflect individual contexts. This dynamic approach allows the location sharing to remain simple in structure while becoming increasingly personalized and informative over time.
Data Source
Figure 1A
Figure 1B
Figure 2
AI summary
Systems and methods are disclosed for managing personalized user location information. The managing comprises: identifying, by a matching engine, one or more personalized geotags, each personalized geotag identifying a specific user and a location of the specific user; determining, by the matching engine, whether there is an overlap between a given one of the personalized geotags and any other geotags; and selecting the geotag that most closely correlates to a given location of the specific user.