US 12,073,428 B2
System and method for automatically retrieving relevant digital advertisements from multiple channels
Tanay Kumar Saha, San Jose, CA (US); Yanbing Xue, Sunnyvale, CA (US); Xiaobo Peng, Bellevue, WA (US); Jayanth Korlimarla, Sunnyvale, CA (US); Musen Wen, Mountain View, CA (US); Wei Shen, Pleasanton, CA (US); Rajesh Garigipati, San Bruno, CA (US); Anant Furia, San Jose, CA (US); Valeriy Pelyushenko, San Jose, CA (US); Chintan Jagdish Rita, Sunnyvale, CA (US); and Ergin Guney, San Bruno, CA (US)
Assigned to Walmart Apollo, LLC, Bentonville, AR (US)
Filed by Walmart Apollo, LLC, Bentonville, AR (US)
Filed on Jan. 30, 2023, as Appl. No. 18/103,125.
Prior Publication US 2024/0257175 A1, Aug. 1, 2024
Int. Cl. G06Q 30/02 (2023.01); G06Q 30/0242 (2023.01); G06Q 30/0273 (2023.01); G06Q 30/0601 (2023.01)
CPC G06Q 30/0244 (2013.01) [G06Q 30/0275 (2013.01); G06Q 30/0625 (2013.01); G06Q 30/0631 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system, comprising:
a non-transitory memory having instructions stored thereon; and
at least one processor operatively coupled to the non-transitory memory, and configured to read the instructions to:
obtain, from a computing device, a search request identifying a query and seeking items to be displayed on a webpage of a website to a user,
search, based on the query, a first database to retrieve a first set of sponsored items associated with the website, wherein the first set of sponsored items are retrieved and ranked based on an optimization of conversion rate,
search, based on the query, a second database to retrieve a second set of sponsored items associated with the website, wherein the second set of sponsored items are retrieved and ranked based on an optimization of click-through rate,
compute, for each sponsored item in the first set and the second set, a relevance score representing a degree of relevancy between the sponsored item and the query,
filter the first set of sponsored items based on their relevance scores and at least one predetermined threshold, to generate a first filtered set of sponsored items,
generate, for each of the first filtered set of sponsored items, a first ranking score representing a likelihood of conversion using a first machine learning model,
select, from the first filtered set, up to a predetermined first number of sponsored items based on their respective first ranking scores, to generate a first selected set of sponsored items,
filter the second set of sponsored items based on their relevance scores and at least one predetermined threshold, to generate a second filtered set of sponsored items,
generate, for each of the second filtered set of sponsored items, a second ranking score representing a likelihood of click using a second machine learning model,
select, from the second filtered set, up to a predetermined second number of sponsored items based on their respective second ranking scores, to generate a second selected set of sponsored items,
generate, based on the first selected set of sponsored items and the second selected set of sponsored items, a ranked list of recommended items based on an advertisement auction mechanism, and
transmit, to the computing device, the ranked list of recommended items in response to the search request.