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:
Nov. 08, 2022

Filed:

Nov. 29, 2018
Applicants:

Yehezkal Shraga Resheff, Jerusalem, IL;

Shimon Shahar, Hasharon, IL;

Oren Sar Shalom, Hasharon, IL;

Yanai Elazar, Hasharon, IL;

Inventors:

Yehezkal Shraga Resheff, Jerusalem, IL;

Shimon Shahar, Hasharon, IL;

Oren Sar Shalom, Hasharon, IL;

Yanai Elazar, Hasharon, IL;

Assignee:

Intuit Inc., Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06Q 30/02 (2012.01); G06F 17/11 (2006.01); G06K 9/62 (2022.01); G06N 20/20 (2019.01); G06F 16/9035 (2019.01);
U.S. Cl.
CPC ...
G06N 20/20 (2019.01); G06F 16/9035 (2019.01); G06F 17/11 (2013.01); G06K 9/6262 (2013.01); G06Q 30/0282 (2013.01);
Abstract

A method includes generating recommendations and user structures by applying a recommender machine learning model to training user information and item information, and generating, from the user structures and by applying a demographic machine learning model, demographic predictions of users represented by the user structures. The method further includes generating a first accuracy measure of the demographic machine learning model based on a first comparison of the demographic predictions with demographics of the users. A recommender loss function is generated based on the first accuracy measure and a second comparison of the recommendations with selections of users, where the recommender loss function uses the first accuracy measure to suppress detectability by the demographic machine learning model. The method further includes updating the recommender machine learning model according to the recommender loss function.


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