Google llc (20240160678). DISTRIBUTING DIGITAL COMPONENTS BASED ON PREDICTED ATTRIBUTES simplified abstract
Contents
- 1 DISTRIBUTING DIGITAL COMPONENTS BASED ON PREDICTED ATTRIBUTES
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 DISTRIBUTING DIGITAL COMPONENTS BASED ON PREDICTED ATTRIBUTES - 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 How does the system ensure user privacy and data security?
- 1.11 What is the scalability of the system for a large number of users?
- 1.12 Original Abstract Submitted
DISTRIBUTING DIGITAL COMPONENTS BASED ON PREDICTED ATTRIBUTES
Organization Name
Inventor(s)
Arne Mauser of Los Altos Hills CA (US)
DISTRIBUTING DIGITAL COMPONENTS BASED ON PREDICTED ATTRIBUTES - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240160678 titled 'DISTRIBUTING DIGITAL COMPONENTS BASED ON PREDICTED ATTRIBUTES
Simplified Explanation
The patent application describes methods, systems, and apparatus for selecting and distributing digital components based on predicted user attributes of users.
- Obtaining data indicating content categories of content accessed by the user
- Making a determination for an aggregate measure of each content category
- Obtaining user attribute prediction data indicating previously predicted user attributes
- Predicting user attributes for the current visit of the user
- Selecting digital components for display based on predicted user attributes
Potential Applications
This technology could be applied in personalized content recommendations, targeted advertising, and user experience customization.
Problems Solved
This technology helps in improving user engagement, increasing click-through rates, and enhancing user satisfaction by providing relevant content.
Benefits
The benefits of this technology include improved user experience, increased user engagement, higher conversion rates, and better targeting of digital content.
Potential Commercial Applications
The potential commercial applications of this technology include digital marketing platforms, e-commerce websites, online publishing platforms, and social media networks.
Possible Prior Art
One possible prior art could be personalized recommendation algorithms used in e-commerce platforms and streaming services to suggest products or content based on user preferences.
Unanswered Questions
How does the system ensure user privacy and data security?
The patent application does not provide details on how user data is protected and secured within the system.
What is the scalability of the system for a large number of users?
The patent application does not address how the system can handle a high volume of users and data processing efficiently.
Original Abstract Submitted
methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting and distributing digital components based on predicted user attributes of users are described. in one aspect, a method includes obtaining data indicating content categories of content of the content pages accessed by the user during the user visits. a determination is made for an aggregate measure of each content category based on a quantity of user visits to content pages of the electronic resource of the publisher that included content classified as belonging to the content category. user attribute prediction data indicating previously predicted user attributes of the user is obtained. user attributes are predicted for the current visit of the user to the electronic resource of the publisher that is further used to select digital components for display with the electronic resource on a client device during the current visit.
