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. 07, 2024

Filed:

Aug. 26, 2019
Applicant:

Visa International Service Association, San Francisco, CA (US);

Inventors:

Maryam Moosaei, San Jose, CA (US);

Yu-San Lin, Mountain View, CA (US);

Hao Yang, San Jose, CA (US);

Assignee:

Visa International Service Association, San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06Q 30/0601 (2023.01); G06N 3/02 (2006.01); G06N 3/04 (2023.01); G06Q 30/02 (2023.01); G06Q 30/0251 (2023.01); G06Q 30/0282 (2023.01); G06Q 30/06 (2023.01); G06T 7/00 (2017.01);
U.S. Cl.
CPC ...
G06Q 30/0631 (2013.01); G06N 3/02 (2013.01); G06N 3/04 (2013.01); G06Q 30/0269 (2013.01); G06Q 30/0282 (2013.01); G06Q 30/06 (2013.01); G06Q 30/0601 (2013.01); G06T 7/0002 (2013.01); G06Q 30/02 (2013.01);
Abstract

Systems, methods, and computer program products for predicting user preference of items in an image process image data associated with a single image with a first branch of a neural network to produce an image embedding, the single image including a set of multiple items; process a user identifier of a user with a second branch of the neural network to produce a user embedding; concatenate the image embedding with the user embedding to produce a concatenated embedding; process the concatenated embedding with the neural network to produce a joint embedding; and generate a user preference score for the set of multiple items from the neural network based on the joint embedding, the user preference score including a prediction of whether the user prefers the set of multiple items.


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