17934854. Online Meta-Learning for Scalable Item-to-Item Relationships simplified abstract (Apple Inc.)
Online Meta-Learning for Scalable Item-to-Item Relationships
Organization Name
Inventor(s)
Dimitrios Bermperidis of Seattle WA (US)
Sofia M. Nikolakaki of San Jose CA (US)
Rabi S. Chakraborty of San Jose CA (US)
Rajesh Kumar of Cupertino CA (US)
Chandrasekar Venkataraman of Los Altos CA (US)
Natalia G. Silveira of Campbell CA (US)
Puja Das of San Francisco CA (US)
Online Meta-Learning for Scalable Item-to-Item Relationships - A simplified explanation of the abstract
This abstract first appeared for US patent application 17934854 titled 'Online Meta-Learning for Scalable Item-to-Item Relationships
Simplified Explanation
The patent application abstract describes a distribution platform interface for a seed item landing page, which includes a recommendation section. The recommendations are generated based on a framework that considers the seed app and relationship type, and can handle multiple relationship types.
- The interface is designed to display recommendations on a seed item landing page.
- Recommendations are selected using a framework that analyzes the seed app and relationship type.
- The framework can handle multiple relationship types for generating recommendations.
Potential Applications
- E-commerce platforms
- Content recommendation systems
- Social media networks
Problems Solved
- Providing personalized recommendations to users
- Enhancing user engagement on platforms
- Improving user experience by suggesting relevant items
Benefits
- Increased user interaction with recommended items
- Higher conversion rates for recommended products
- Enhanced user satisfaction with personalized recommendations
Original Abstract Submitted
A distribution platform interface is presented with respect to a seed item landing page. The seed item landing page includes a recommendation section. The items listed in the recommendation section are selected from a framework that is configured to provide recommendations of candidate items based on a given seed app and relationship type, and which is configured to handle multiple relationship types.
