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:
Feb. 01, 2022

Filed:

Mar. 30, 2018
Applicant:

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

Inventors:

Chi-Yi Kuan, Fremont, CA (US);

Shen Huang, San Jose, CA (US);

Yu Wang, Sunnyvale, CA (US);

Yongzheng Zhang, San Jose, CA (US);

Paul Ko, San Francisco, CA (US);

Shady Elasra, San Francisco, CA (US);

Fanbin Bu, Fremont, CA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 5/04 (2006.01); G06N 99/00 (2019.01); G06N 20/00 (2019.01); H04L 29/08 (2006.01);
U.S. Cl.
CPC ...
G06N 5/04 (2013.01); G06N 20/00 (2019.01); H04L 67/306 (2013.01);
Abstract

Techniques are provided for predicting talent flow to and/or from a geographical region. In one technique, multiple entity profiles are stored and analyzed to generate training data that is labeled indicating whether a corresponding entity has moved to or moved from a region. A machine-learned prediction model is generated or trained based on the training data. Using the machine-learned prediction model, a prediction is made whether, for each entity corresponding to another entity profile, that entity will move to or move from a particular geographic region. Based on multiple predictions, a number of entities that are predicted to move to or move from the particular geographic region is determined. Talent flow data that is based on the number of entities is presented on a computer display.


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