User Data Sharing via Local Medium Network
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Solution Overview
Problem
Current technologies face challenges in sharing user behavior information across different service platforms due to issues with user recognition, information interaction, and categorized statistics, leading to a lack of effective solutions for passing user behavior information between the same user entities on various platforms.
Innovation Solution
A user data sharing method and device that acquires and constructs a local medium network using multiple pieces of medium information to determine a trusted account, allowing for the sharing of user behavior information by normalizing and iteratively calculating edge weights to sort user accounts and media, thereby accurately matching user accounts across platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If user data is shared across different service platforms, then data utility and user behavior information sharing are improved, but user privacy security and data accuracy deteriorate
Solution Approach 1:
The patent introduces a medium network as an intermediary layer between different service platforms. This medium network contains medium information (device identifiers, network identifiers, location information) that acts as a mediator to associate user accounts across platforms without directly exposing sensitive user data. The medium network enables indirect user identification while maintaining privacy security, resolving the contradiction between data sharing and privacy protection.
Solution Approach 2:
The patent creates a virtual copy of user identity through medium information rather than using real user identifiers. Instead of directly sharing sensitive user account information across platforms, the system generates medium information that copies the essential identifying characteristics while maintaining security. This virtual identity copy enables data sharing while protecting original user privacy.
2Measurement precision
If multiple pieces of medium information are used to identify users, then user recognition accuracy is improved, but system complexity and calculation overhead increase
Solution Approach 1:
The patent performs preliminary actions by pre-collecting and organizing medium information (device identifiers, network identifiers, location information) during normal user operations. This medium information is stored in advance in the medium network before actual user identification is needed. When user recognition is required, the system can quickly query pre-organized medium information without performing complex real-time analysis, thus improving accuracy while managing complexity.
Solution Approach 2:
The patent segments the user identification process into multiple independent components: collecting different types of medium information (device identifiers, network identifiers, location information), storing them separately in the medium network, and then combining them through iterative calculation. This segmentation allows the system to handle complex multi-factor identification by breaking it down into manageable, independent data collection and processing steps.
3Measurement precision
If iterative calculation is performed on edge weights, then user account matching accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The patent implements periodic action through iterative calculation of edge weights in the medium network. Instead of performing a single complex calculation, the system repeatedly updates edge weights connecting medium information to user accounts in multiple iterations. Each iteration refines the matching accuracy by adjusting weights based on observed relationships. This periodic refinement process improves matching precision while allowing the system to converge to stable results, balancing accuracy with processing efficiency.
Data Source
AI summary
A user data sharing method comprises: acquiring information of a query medium; obtaining, according to the information of the query medium, at least one user account related to the query medium and relationship information of the at least one user account from a medium network, the relationship information of the user account comprising: a strength of a relationship between the user account and the query medium and a strength of a relationship between the user account and other user accounts; constructing a local medium network by using the obtained at least one user account and relationship information of the at least one user account; determining a trusted account from the at least one user account by using the local medium network; and acquiring user data of the trusted account and outputting the user data of the trusted account as the user data corresponding to the information of the query medium.