Microsoft technology licensing, llc (20240119484). PRIVACY-PRESERVING RULES-BASED TARGETING USING MACHINE LEARNING simplified abstract
Contents
- 1 PRIVACY-PRESERVING RULES-BASED TARGETING USING MACHINE LEARNING
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 PRIVACY-PRESERVING RULES-BASED TARGETING USING MACHINE LEARNING - 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 RULES-BASED TARGETING USING MACHINE LEARNING
Organization Name
microsoft technology licensing, llc
Inventor(s)
PRIVACY-PRESERVING RULES-BASED TARGETING USING MACHINE LEARNING - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240119484 titled 'PRIVACY-PRESERVING RULES-BASED TARGETING USING MACHINE LEARNING
Simplified Explanation
The patent application describes techniques for privacy-preserving rules-based targeting using machine learning. Entities are ranked using a machine learning model, and values of targetable features are ordered and sorted into bins based on their values. A targeting rule is established based on the selected bin for each feature.
- Entities are ranked using a machine learning model
- Values of targetable features are ordered and sorted into bins
- A targeting rule is established based on the selected bin for each feature
Potential Applications
The technology can be applied in targeted advertising, personalized recommendations, and content filtering.
Problems Solved
This technology addresses the challenge of targeting specific entities based on their features while preserving privacy.
Benefits
The benefits of this technology include improved targeting accuracy, enhanced privacy protection, and efficient rule-based targeting.
Potential Commercial Applications
Potential commercial applications include digital marketing, e-commerce platforms, and online content platforms.
Possible Prior Art
One possible prior art could be the use of machine learning for targeted advertising in online platforms.
Unanswered Questions
How does this technology handle dynamic changes in entity features over time?
The patent application does not provide information on how the system adapts to changes in entity features.
What are the potential limitations of using machine learning for privacy-preserving targeting?
The patent application does not discuss any potential drawbacks or limitations of using machine learning for privacy-preserving targeting.
Original Abstract Submitted
techniques are described herein that are capable of providing privacy-preserving rules-based targeting using machine learning. ranks are assigned to entities using a machine learning model. values of each targetable feature associated with the respective entities are ordered. for each targetable feature, the entities are sorted among bins based on the values of the feature associated with the respective entities. for each targetable feature, a bin is selected from the bins that are associated with the feature based on the selected bin including more entities having respective ranks that are within a designated range than each of the other bins that are associated with the feature. a targeting rule is established, indicating a prerequisite for targeting an entity. the prerequisite indicating that the value of each targetable feature associated with the entity is included in a respective interval associated with the selected bin for the feature.