18296504. RECOMMENDATION SERVICE USING BLIND SIGNATURES simplified abstract (SAP SE)
Contents
RECOMMENDATION SERVICE USING BLIND SIGNATURES
Organization Name
Inventor(s)
Shashank Mohan Jain of Bangalore (IN)
Srinivasa Reddy Challa of Guntur (IN)
RECOMMENDATION SERVICE USING BLIND SIGNATURES - A simplified explanation of the abstract
This abstract first appeared for US patent application 18296504 titled 'RECOMMENDATION SERVICE USING BLIND SIGNATURES
The abstract describes a process where a user requests to use a recommendation service, providing personal data encrypted with a commuting function, and clear text account details. A blind trust is established with the user, and the recommendation service signs the onboarding request and sends it back to the user for blind onboarding. A consumption request is then received from the user, and the recommendation service updates a user-item matrix to provide item recommendations based on the user's preferences.
- User requests to use recommendation service
- Personal data encrypted with commuting function
- Blind trust established with user
- Recommendation service signs onboarding request
- User performs blind onboarding
- Consumption request received from user
- User-item matrix updated for item recommendations
- Approved credits document expired after consumption
Potential Applications: - Personalized recommendation systems - Secure data encryption and transmission - User trust and privacy management
Problems Solved: - Ensuring user privacy and data security - Efficient recommendation service operation - Seamless user experience in utilizing recommendation services
Benefits: - Enhanced user trust and privacy protection - Personalized and accurate item recommendations - Streamlined onboarding and consumption processes
Commercial Applications: Title: Secure Recommendation Service for Personalized User Experiences This technology can be applied in e-commerce platforms, streaming services, and social media platforms to enhance user engagement and satisfaction through personalized recommendations and secure data handling.
Questions about the technology: 1. How does the blind trust mechanism enhance user privacy and trust in the recommendation service? 2. What are the potential challenges in implementing the user-item matrix for item recommendations in real-time systems?
Original Abstract Submitted
An onboarding request is received from a user to utilize a recommendation service. The onboarding request contains personal data (including an onboarding user identifier and a serial number requesting a stated number of credits), encrypted with a commuting function C, along with clear text account details. A blind trust is established with the user, and the recommendation service signs the onboarding request with a signing function S and sends the signed onboarding request to the user to perform a blind onboarding of the user. A consumption request is then received (e.g., a call to get recommendations) from the user including a consumption user identifier and an approved credits document. The recommendation service can then update a user-item matrix that maps user identifiers with available items and transmit an item recommendation to the user, based on the user-item matrix, and expire the approved credits document by a consumption amount.
