The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
May. 14, 2024

Filed:

Oct. 26, 2021
Applicant:

Microsoft Technology Licensing, Llc, Redmond, WA (US);

Inventors:

Kiran Tomlinson, Ithaca, NY (US);

Longqi Yang, Issaquah, WA (US);

Mengting Wan, Bellevue, WA (US);

Cao Lu, Bellevue, WA (US);

Brent Jaron Hecht, Redmond, WA (US);

Jaime Teevan, Bellevue, WA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06Q 10/00 (2023.01); G06N 5/00 (2023.01); G06N 5/022 (2023.01); G06N 5/04 (2023.01); G06Q 10/063 (2023.01);
U.S. Cl.
CPC ...
G06Q 10/063 (2013.01); G06N 5/022 (2013.01); G06N 5/04 (2013.01);
Abstract

An enterprise system server, a computer-readable storage medium, and a method for targeted training of inductive multi-organization recommendation models for enterprise applications are described herein. The method includes receiving enterprise application data from remote organization computing systems executing the enterprise application, training per-organization recommendation models for a subset of the organizations, and validating each per-organization recommendation model on enterprise application data corresponding to one or more other organizations. The method also includes calculating a transferability metric for each per-organization recommendation model based on results obtained during validation, determining a specified number of organizations including the best-transferring per-organization recommendation models based on the calculated transferability metrics, and training an inductive multi-organization recommendation model using the enterprise application data from the specified number of organizations. The method further includes utilizing the trained inductive multi-organization recommendation model to provide user recommendations to the remote organization computing systems during execution of the enterprise application.


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