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.
Patent No.:
Date of Patent:
Oct. 14, 2025
Filed:
Jan. 21, 2022
Walmart Apollo, Llc, Bentonville, AR (US);
Da Xu, Sunnyvale, CA (US);
Jianpeng Xu, San Jose, CA (US);
Sushant Kumar, San Jose, CA (US);
Evren Korpeoglu, San Jose, CA (US);
Kannan Achan, Saratoga, CA (US);
WALMART APOLLO, LLC, Bentonville, AR (US);
Abstract
Systems and methods including one or more processors and one or more non-transitory computer readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform: receiving a user request via a graphical user interface, the user request corresponding to a user search query for a product; determining whether a first processing machine of the system is operating in a first processing mode or a second processing mode; when the first processing machine is determined to be operating in the first processing mode, analyzing the user request via the first processing machine and using a process, to identify a candidate recommendation system to utilize by: determining a randomized strategy for one or more candidate recommendation systems based on a ratio of a number of the one or more candidate recommender systems, the randomized strategy to be stored in a collected history data; determining model parameters based on the collected history data; and determining the candidate recommendation system from the one or more candidate recommendation systems as a candidate recommendation system with a maximum value for a reward model based on the user request; processing the user request with the candidate recommendation system to identify recommended products to display to the user; and transmitting instructions to modify the graphical user interface to display the recommended products to the user.