Patent ID: 11954108
Assignee: WALMART APOLLO, LLC
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A system comprising:
a database; and
a computing device communicatively coupled to the database, the computing device configured to:
receive a query and data identifying a plurality of items;
obtain, from the database, first item attributes for each of the plurality of items;
generate a semantic relevancy score for each of the plurality of items by applying a first machine learning model to corresponding first item attributes and the query, wherein the first machine learning model is configured to combine a plurality of attribute scores, wherein at least one of the plurality of attribute scores is determined by matching attributes for each of the plurality of items based on a textual comparison between the corresponding first item attributes and the query, and wherein the first machine learning model is generated from search query-item pair data labelled with a corresponding semantic relevancy score;
generate a blended relevancy score by combining the semantic relevancy score and a search relevancy score of each of the plurality of items;
generate ranking data based on the blended relevancy score for each of the plurality of items;
determine an alignment of the ranking data of the plurality of items with a previously generated ranking of the plurality of items based on the query applied by the first machine learning model previously, wherein the alignment is representative of ranking positions in the ranking data of the plurality items as compared to ranking positions in the previously generated ranking;
generate updated search query-item pair data for a corresponding one of the plurality of items when the alignment is less than a predetermined threshold, wherein the updated search query-item pairs are stored in a labelled corpus comprising data structures stored in the database including search query-item pairs labelled with the generated semantic relevancy score; and
generate a second machine learning model configured to combine a plurality of attribute scores, wherein the second machine learning model is trained, in part, from the labelled corpus.