17972408. SUPERPOSITION-BASED CONTENT SERVING simplified abstract (MICROSOFT TECHNOLOGY LICENSING, LLC)
Contents
SUPERPOSITION-BASED CONTENT SERVING
Organization Name
MICROSOFT TECHNOLOGY LICENSING, LLC
Inventor(s)
Albert Hwang of McKinney TX (US)
Jianlong Zhang of Sunnyvale CA (US)
Muhammad Hassan Khan of Dublin CA (US)
SUPERPOSITION-BASED CONTENT SERVING - A simplified explanation of the abstract
This abstract first appeared for US patent application 17972408 titled 'SUPERPOSITION-BASED CONTENT SERVING
The disclosed technologies process requests by removing user identifiers, correlating anonymized data with superposition data from a machine learning model, and matching it with real-time content for distribution.
- Receive request with user identifier and slot metadata
- Anonymize request data by removing user identifier
- Obtain superposition data from machine learning model
- Match superposition data with real-time content for distribution
- Select content distribution based on superposition data
- Initiate selected content distribution to the slot in response to the request
- Potential Applications:**
- Real-time content distribution - Personalized content delivery - Data anonymization techniques
- Problems Solved:**
- Efficient content matching - User privacy protection - Enhanced user experience
- Benefits:**
- Improved content delivery - Enhanced user privacy - Streamlined request processing
- Commercial Applications:**
Title: Real-time Content Distribution Technology This technology can be utilized in online advertising, content streaming services, and personalized recommendation systems to optimize content delivery and enhance user engagement.
- Questions about Real-time Content Distribution Technology:**
1. How does this technology improve user privacy while delivering personalized content?
- This technology anonymizes user data to protect privacy while still providing personalized content recommendations.
2. What are the potential challenges in implementing real-time content distribution on a large scale?
- The main challenges may include processing a high volume of requests efficiently and ensuring accurate content matching in real-time.
Original Abstract Submitted
Embodiments of the disclosed technologies receive a request including a user identifier and metadata associated with a slot available at a user system, remove the user identifier from the request to produce anonymized request data, receive, from a machine learning model, superposition data that correlates with the anonymized request data, send the superposition data for the anonymized request data to a real-time content-to-request matching process, receive, from the real-time content-to-request matching process, an identifier that identifies a content distribution selected based on the superposition data, and initiate the selected content distribution through the network to the slot in response to the request.
