US 12,236,469 B2
Determining brand affinity of users
Sushant Kumar, Sunnyvale, CA (US); Hyun Duk Cho, San Francisco, CA (US); Kannan Achan, Saratoga, CA (US); and Venkata Syam Prakash Rapaka, Cupertino, CA (US)
Assigned to WALMART APOLLO, LLC, Bentonville, AR (US)
Filed by Walmart Apollo, LLC, Bentonville, AR (US)
Filed on Aug. 1, 2022, as Appl. No. 17/878,306.
Application 17/878,306 is a continuation of application No. 16/260,485, filed on Jan. 29, 2019, granted, now 11,403,690.
Claims priority of provisional application 62/623,477, filed on Jan. 29, 2018.
Prior Publication US 2022/0383390 A1, Dec. 1, 2022
Int. Cl. G06Q 30/0601 (2023.01); G06Q 30/0241 (2023.01); G06Q 30/0251 (2023.01)
CPC G06Q 30/0631 (2013.01) [G06Q 30/0255 (2013.01); G06Q 30/0277 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system comprising:
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 functions comprising:
identifying a first user who has brand affinities about a first product brand or a first product brand category by using two models, wherein:
(a) a model one determines an affinity to a particular first product brand, wherein when a first result of the model one exceeds a first predetermined threshold value for a product brand within a predetermined period of time, the first result is a first probability score; and
(b) a model two determines an affinity to a particular first product brand category;
analyzing whether the first user has affinities for a similar product brand or a similar product brand category by using a model three neural network to determine an affinity for the similar product brand or the similar product brand category, wherein the similar product brand is similar to the first product brand, and wherein the similar product brand category is similar to the first product brand category;
determining whether to display first recommendations for the first product brand or the first product brand category to the first user based on results from the two models;
determining whether to display second recommendations for the similar product brand or the similar product brand category to the first user based on output from the model three neural network; and
transmitting instructions to display the first and second recommendations to the first user.