US 12,169,512 B2
Search analysis and retrieval via machine learning embeddings
Laura D. Hamilton, Chicago, IL (US); Vinit Garg, Fremont, CA (US); Ayush Tomar, Morgan Hill, CA (US); Martin R. Linenweber, San Francisco, CA (US); Preet Kamal S. Bawa, Vernon Hills, IL (US); David Armbrust, Glen Ellyn, IL (US); Rupesh Kartha, San Ramon, CA (US); and Lun Yu, San Francisco, CA (US)
Assigned to UnitedHealth Group Incorporated, Minnetonka, MN (US)
Filed by UnitedHealth Group Incorporated, Minnetonka, MN (US)
Filed on Oct. 21, 2022, as Appl. No. 17/971,491.
Claims priority of provisional application 63/366,425, filed on Jun. 15, 2022.
Prior Publication US 2023/0409614 A1, Dec. 21, 2023
Int. Cl. G06F 16/33 (2019.01); G06F 16/332 (2019.01); G06F 16/387 (2019.01)
CPC G06F 16/3325 (2019.01) [G06F 16/3334 (2019.01); G06F 16/387 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
receiving, by one or more processors, a query input; and
generating, by the one or more processors and using a search engine machine learning model, a prediction-based action for the query input by:
(i) generating a plurality of query input embeddings of the query input that respectively correspond to a plurality of content categories. wherein the plurality of content categories comprises a geospatial content category and the plurality of query input embeddings comprises a query geohash embedding corresponding to the query input,
(ii) identifying a plurality of initial search result sets, using a k-Nearest-Neighbor (KNN) search, respectively corresponding to the plurality of content categories based at least in part on a comparison between the plurality of query input embeddings and a plurality of search engine repository item embeddings,
(iii) generating, via N hops within a semantic graph starting from a plurality of nodes respectively associated with the plurality of initial search result sets, a plurality of related search results, and
(iv) generating the prediction-based action for the query input based at least in part on the plurality of related search results.