Microsoft technology licensing, llc (20240338413). CUSTOMIZED RECOMMENDATION GENERATION USING ENTERPRISE DATA ANALYSIS AND INFERENCE simplified abstract

CUSTOMIZED RECOMMENDATION GENERATION USING ENTERPRISE DATA ANALYSIS AND INFERENCE

Organization Name

microsoft technology licensing, llc

Inventor(s)

Eivind Berg Fosse of Oslo (NO)

Ute Katja Schiehlen of Oslo (NO)

Sergey Putilin of Oslo (NO)

Tinus Sola Flagstad of Oslo (NO)

Mohammadreza Bonyadi of Trondheim (NO)

Ola Saetrom of Oslo (NO)

Espen Trautmann Sommerfelt of Oslo (NO)

Torbjørn Helvik of Oslo (NO)

CUSTOMIZED RECOMMENDATION GENERATION USING ENTERPRISE DATA ANALYSIS AND INFERENCE - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240338413 titled 'CUSTOMIZED RECOMMENDATION GENERATION USING ENTERPRISE DATA ANALYSIS AND INFERENCE

The patent application describes systems and methods for inferring the favorite authors and collaborators of a user by analyzing document access and contributor data.

• Storing an enterprise authorship database
• Identifying a document accessed by a user
• Determining contributors to the document
• Generating a contribution score for each contributor
• Determining one or more authors of the document
• Creating an authorship record by associating user identifiers with authors
• Updating the enterprise authorship database with the authorship record

Potential Applications: - Personalized author recommendations for users - Enhanced collaboration suggestions for researchers - Improved content discovery on platforms

Problems Solved: - Identifying favorite authors and collaborators of users - Providing tailored recommendations based on user behavior - Enhancing user experience with relevant content suggestions

Benefits: - Increased user engagement - Enhanced user satisfaction - Improved content relevance

Commercial Applications: Title: Personalized Author Recommendation System This technology can be used in online platforms, research databases, and content management systems to provide personalized author and collaborator recommendations, enhancing user experience and engagement.

Questions about the technology: 1. How does this system ensure data privacy and security for user information? 2. Can this technology be integrated with existing recommendation systems for seamless user experience?

Original Abstract Submitted

systems and methods for inferring the favorite authors and collaborators of a user are provided. the method includes storing an enterprise authorship database, identifies a document accessed by a user identifier (uid), identifying contributors to the identified document, generating a contribution score for each contributor of the identified contributors, based on each generated contribution score, determining one or more authors of the identified document, creating an authorship record by associating uids of the determined one or more authors with the identified document, and updating the enterprise authorship database with the created authorship record, wherein the authorship record is used to identify a relationship between the uid and the determined one or more authors and generate a recommendation for the uid based on the identified relationship.