Google llc (20240163259). PRIVACY PRESERVING GROUP-BASED CONTENT DISTRIBUTION simplified abstract
Contents
- 1 PRIVACY PRESERVING GROUP-BASED CONTENT DISTRIBUTION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 PRIVACY PRESERVING GROUP-BASED CONTENT DISTRIBUTION - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
PRIVACY PRESERVING GROUP-BASED CONTENT DISTRIBUTION
Organization Name
Inventor(s)
Michael William Daub of Woodinville WA (US)
Robert F. Day of Bellevue WA (US)
Arthur Asuncion of Bothell WA (US)
PRIVACY PRESERVING GROUP-BASED CONTENT DISTRIBUTION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240163259 titled 'PRIVACY PRESERVING GROUP-BASED CONTENT DISTRIBUTION
Simplified Explanation
The patent application describes a method for displaying digital components on client devices based on predicted user attributes of users.
- Updating a list of user group identifiers for a user on a client device.
- Determining a score for each user attribute based on the quantity of user groups identified in the list of group identifiers for the user.
- Sending a digital component request to a content distribution system based on the data representing the list of user-group identifiers.
- Receiving digital component data identifying a set of digital components selected based on the data of the digital component request.
Potential Applications
This technology could be applied in personalized advertising, content recommendation systems, and targeted marketing campaigns.
Problems Solved
This technology solves the problem of delivering relevant digital content to users based on their predicted attributes and interests.
Benefits
The benefits of this technology include improved user engagement, increased click-through rates, and enhanced user experience.
Potential Commercial Applications
The potential commercial applications of this technology include digital marketing platforms, e-commerce websites, and online advertising networks.
Possible Prior Art
One possible prior art for this technology could be personalized recommendation systems used by streaming services like Netflix or music platforms like Spotify.
Unanswered Questions
How does the system ensure user privacy and data security while predicting user attributes?
The system may use encryption techniques or anonymized data to protect user information.
What measures are in place to prevent bias or discrimination in the prediction of user attributes?
The system may employ algorithms that are designed to be fair and unbiased, with regular audits to ensure compliance with ethical standards.
Original Abstract Submitted
methods, systems, and apparatus, including computer programs encoded on a computer storage medium for displaying digital components on client devices based on predicted user attributes of users are described. in one aspect, a method includes updating, at a client device of a user, a list of user group identifiers for the user to include a particular user group identifier that identifies a particular user group. a determination is made, for each user attribute of multiple user attributes, a score based on a quantity of user groups identified in the list of group identifiers for the user that include, as a membership attribute, the user attribute. a digital component request including data representing the list of user-group identifiers is sent to a content distribution system. digital component data identifying a set of digital components selected based on the data of the digital component request is received.
