US 12,235,912 B1
Domain-aware autocomplete
Ramin Anushiravani, San Carlos, CA (US); Yizhao Ni, Centennial, CO (US); Harsh M. Maheshwari, Irving, TX (US); Cem Unsal, Alameda, CA (US); and Micah David Ketola, Jersey City, NJ (US)
Assigned to Optum, Inc., Minnetonka, MN (US)
Filed by Optum, Inc., Minnetonka, MN (US)
Filed on Jan. 18, 2024, as Appl. No. 18/416,276.
Claims priority of provisional application 63/578,517, filed on Aug. 24, 2023.
Int. Cl. G06F 16/9532 (2019.01); G06F 16/951 (2019.01); G06F 40/58 (2020.01)
CPC G06F 16/9532 (2019.01) [G06F 16/951 (2019.01); G06F 40/58 (2020.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
generating, by one or more processors and using a domain-aware autocomplete model, a label for an autocomplete suggestion based on a set of keywords within an autocomplete suggestion training dataset associated with a target domain source;
generating, by the one or more processors and using a weak-labeling model, an updated label for the autocomplete suggestion by decorrelating the set of keywords from the label;
generating, by the one or more processors and using a sentence classification model, a category for the autocomplete suggestion based on the updated label;
generating, by the one or more processors and using the domain-aware autocomplete model, a suggestion-category pair (SCP) based on the autocomplete suggestion and the category for the autocomplete suggestion; and
initiating, by the one or more processors, a performance of a search query resolution based on the SCP.