Google llc (20240202360). PRIVACY PRESERVING CUSTOM EMBEDDINGS simplified abstract
Contents
- 1 PRIVACY PRESERVING CUSTOM EMBEDDINGS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 PRIVACY PRESERVING CUSTOM EMBEDDINGS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Prior Art
- 1.11 Frequently Updated Research
- 1.12 Questions about the Technology
- 1.13 Original Abstract Submitted
PRIVACY PRESERVING CUSTOM EMBEDDINGS
Organization Name
Inventor(s)
Gang Wang of Frederick MD (US)
Alexander E. Mayorov of Kirkland WA (US)
PRIVACY PRESERVING CUSTOM EMBEDDINGS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240202360 titled 'PRIVACY PRESERVING CUSTOM EMBEDDINGS
Simplified Explanation
The patent application describes methods, systems, and apparatus for selecting and distributing digital components to client devices while protecting user privacy and confidential data.
- The method involves receiving a digital component request from a user's client device, including user embeddings indicating the relevance of features to the user for multiple content platforms.
- Each user embedding is input into an isolated execution environment hosted by a secure distribution system corresponding to the content platform, generating digital component selection data.
- The secure distribution system receives the selection data from each isolated execution environment.
Key Features and Innovation
- Secure distribution system for selecting and distributing digital components.
- User embeddings with weights indicating feature relevance for personalized content selection.
- Isolated execution environments for each content platform to protect user privacy and data.
Potential Applications
This technology can be applied in digital content platforms, online advertising, personalized recommendations, and data protection systems.
Problems Solved
- Protecting user privacy and confidential data.
- Personalizing content selection based on user preferences.
- Efficient distribution of digital components to client devices.
Benefits
- Enhanced user privacy and data security.
- Improved user experience with personalized content recommendations.
- Efficient and targeted distribution of digital components.
Commercial Applications
- Digital content platforms
- Online advertising companies
- Data protection services
- Personalized recommendation systems
Prior Art
Readers can explore prior art related to secure content distribution systems, personalized recommendation algorithms, and data privacy protection technologies.
Frequently Updated Research
Stay updated on research related to secure content distribution, user privacy protection, and personalized recommendation systems.
Questions about the Technology
How does the technology ensure user privacy and data protection?
The technology utilizes isolated execution environments and user embeddings to protect user data and privacy while providing personalized content recommendations.
What are the potential commercial applications of this technology?
The technology can be applied in digital content platforms, online advertising, data protection services, and personalized recommendation systems.
Original Abstract Submitted
methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting and distributing digital components to client devices in ways that protect user privacy and confidential data of content platforms and/or digital component providers are described. in one aspect, a method includes receiving, by a secure distribution system and from a client device of a user, a digital component request that includes, for each of multiple content platforms that distribute digital components to users, a corresponding user embedding comprising weights indicative of the relevance of multiple features to the user. the secure distribution system provides each user embedding as input to a respective isolated execution environment for the content platform corresponding to the user embedding, wherein the secure distribution system hosts each isolated execution environment. digital component selection data generated based on the user embedding is received from each isolated execution environment.
