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:
Mar. 26, 2024

Filed:

Jan. 28, 2019
Applicant:

Walmart Apollo, Llc, Bentonville, AR (US);

Inventors:

Kannan Achan, Saratoga, CA (US);

Sushant Kumar, Sunnyvale, CA (US);

Kaushiki Nag, Santa Clara, CA (US);

Venkata Syam Prakash Rapaka, Cupertino, CA (US);

Assignee:

WALMART APOLLO, LLC, Bentonville, AR (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 16/56 (2019.01); G06F 16/21 (2019.01); G06F 16/50 (2019.01); G06F 16/535 (2019.01); G06F 16/9535 (2019.01); G06N 3/08 (2023.01);
U.S. Cl.
CPC ...
G06F 16/535 (2019.01); G06F 16/214 (2019.01); G06F 16/50 (2019.01); G06F 16/56 (2019.01); G06F 16/9535 (2019.01); G06N 3/08 (2013.01);
Abstract

A method including training a recurrent neural network model to create a trained model based at least in part on: (a) first images associated with first items on a website, (b) first search terms used by users of the website to search for the first items on the website, and (c) personal features of the users. The method also can include receiving an input image that was uploaded by a current user. The method additionally can include obtaining a user encoded representation vector for the current user based on a set of personal features of the current user. The method further can include generating an image encoded representation vector for the input image. The method additionally can include deriving search terms that are personalized to the current user for the one or more items depicted in the input image, using the trained model and based on the user encoded representation vector for the current user and the image encoded representation vector for the input image. Other embodiments are disclosed.


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