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:
Jun. 28, 2022
Filed:
Jan. 31, 2019
Walmart Apollo, Llc, Bentonville, AR (US);
Anthony Soohoo, Palo Alto, CA (US);
Vijay Raghavendra, San Jose, CA (US);
Charles Myslinsky, Glen Ridge, NJ (US);
Harman Kochar, San Mateo, CA (US);
Abilash Amarthaluri, San Jose, CA (US);
Ashish Gupta, Lucknow, IN;
Karthik Deivasigamani, Chennai, IN;
Behzad Ahmadi, San Jose, CA (US);
Sreyash D. Kenkre, Bengaluru, IN;
Rohit Deep, Union City, CA (US);
Zuzar Fakhruddin Nafar, Mountain View, CA (US);
Omer Ovenc, San Jose, CA (US);
Venkatesh Kandaswamy, San Ramon, CA (US);
Arvind Senthil Kumaran, Sunnyvale, CA (US);
Suleman Ashfaq, San Francisco, CA (US);
WALMART APOLLO, LLC, Bentonville, AR (US);
Abstract
A system can include one or more processors and non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform a method for determining one or more substitutes for a product requested in an inquiry from a user. The method comprises one or more of the steps including receiving an inquiry from a user, which comprises a requested product; extracting one or more attributes of the requested product based on the inquiry; determining a context of the inquiry; and determining one or more substitutes for the requested product from an inventory database based on a distance between the requested product and each substitute of the one or more substitutes, as projected in a product graph relating to a domain of the requested product and the context of the inquiry. In many embodiments, the product graph relating to the domain is generated by a machine learning module configured to dynamically learn information about the domain from various sources, including one or more expert opinions, the inventory database, and/or public records; and dynamically build the product graph according to the information about the domain. An exemplary machine learning module can be configured to dynamically build the product graph by: creating one or more product categories in the domain; extracting one or more entity nodes from the one or more product categories based on the information about the domain; and build one or more connections, including an entity-entity connection between each pair of related entity nodes, a product-entity connection between each product node and each of one or more entity nodes associated with the each product node, and a product-product connection between each pair of related product nodes. Other embodiments are disclosed.