View source for 18097892. DATA TRANSMISSION BETWEEN TWO SYSTEMS TO IMPROVE OUTCOME PREDICTIONS simplified abstract (META PLATFORMS, INC.)

=DATA TRANSMISSION BETWEEN TWO SYSTEMS TO IMPROVE OUTCOME PREDICTIONS=


==Organization Name==

[[:Category:META PLATFORMS, INC.|META PLATFORMS, INC.]]


[[Category:META PLATFORMS, INC.]]

==Inventor(s)==

[[:Category:Andrew Donald Yates of San Francisco CA (US)|Andrew Donald Yates of San Francisco CA (US)]][[Category:Andrew Donald Yates of San Francisco CA (US)]]

[[:Category:Gunjit Singh of San Francisco CA (US)|Gunjit Singh of San Francisco CA (US)]][[Category:Gunjit Singh of San Francisco CA (US)]]

[[:Category:Kurt Dodge Runke of Los Altos CA (US)|Kurt Dodge Runke of Los Altos CA (US)]][[Category:Kurt Dodge Runke of Los Altos CA (US)]]

==DATA TRANSMISSION BETWEEN TWO SYSTEMS TO IMPROVE OUTCOME PREDICTIONS - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18097892 titled 'DATA TRANSMISSION BETWEEN TWO SYSTEMS TO IMPROVE OUTCOME PREDICTIONS

==Simplified Explanation==

The abstract describes a system that generates predicted outcomes for a content distribution program, adjusts these predictions based on feedback from a third-party system, and updates the content distribution program accordingly.

* The online system generates predicted outcomes for content distribution.
* Predicted outcomes are transmitted to a third-party system for feedback.
* The third-party system provides prediction improvement data to adjust errors in the predicted outcomes.
* The online system updates the content distribution program based on the feedback received.
* Content is then distributed to users based on the updated program.

== Potential Applications ==
This technology could be applied in various industries such as marketing, advertising, and e-commerce to optimize content distribution strategies and improve user engagement.

== Problems Solved ==
This technology helps in predicting outcomes of content presentations, adjusting errors in predictions, and updating content distribution programs for better performance.

== Benefits ==
The system allows for more accurate predictions, improved content distribution strategies, and enhanced user experiences, leading to increased engagement and conversion rates.

== Potential Commercial Applications ==
Potential commercial applications of this technology include digital marketing platforms, online advertising networks, and e-commerce websites looking to optimize their content distribution strategies.

== Possible Prior Art ==
One possible prior art for this technology could be predictive analytics software used in marketing and advertising to forecast user behavior and optimize content delivery strategies.

=== Unanswered Questions ===

=== How does the system handle real-time feedback from users to further improve predictions? ===
The system could potentially incorporate real-time user feedback data to continuously refine its predictions and enhance the content distribution program.

=== What measures are in place to ensure data privacy and security when transmitting predicted outcomes to third-party systems? ===
The system may implement encryption protocols and data anonymization techniques to protect the privacy and security of the predicted outcomes shared with third-party systems.


==Original Abstract Submitted==

An online system generates predicted outcomes for a content distribution program that distributes content to users of the online system, the predicted outcome indicating a likelihood for the occurrence of an outcome of a content presentation. The online system transmits the one or more predicted outcomes to the third-party system, and receives prediction improvement data from the third-party system, the prediction improvement data indicating an adjustment to errors in the predicted outcomes based on a prediction by the third-party system. The online system updates the properties of a content distribution program based on the prediction improvement data, the updated content distribution program causing the online system to generate new predicted outcomes based on the prediction improvement data in content presentation opportunities. The online system also transmits content to users of the online system based on the updated content distribution program.



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