US 11,914,665 B2
Multi-modal machine-learning model training for search
Matvey Kapilevich, New York, NY (US); Margarita R. Savova, Jersey City, NJ (US); Anup Bandigadi Rao, San Jose, CA (US); Tung Thanh Mai, San Jose, CA (US); Lakshmi Shivalingaiah, San Francisco, CA (US); Liron Goren Snai, Sunnyvale, CA (US); Charles Menguy, Brooklyn, NY (US); Vijeth Lomada, San Francisco, CA (US); Moumita Sinha, Cupertino, CA (US); and Harleen Sahni, Washington, DC (US)
Assigned to Adobe Inc., San Jose, CA (US)
Filed by Adobe Inc., San Jose, CA (US)
Filed on Feb. 18, 2022, as Appl. No. 17/675,290.
Prior Publication US 2023/0267158 A1, Aug. 24, 2023
Int. Cl. G06F 16/248 (2019.01); G06F 16/9538 (2019.01); G06F 16/28 (2019.01); G06F 16/901 (2019.01); G06N 20/00 (2019.01)
CPC G06F 16/9538 (2019.01) [G06F 16/248 (2019.01); G06F 16/283 (2019.01); G06F 16/9024 (2019.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. In a digital medium machine-learning model training environment for search, a method implemented by a computing device, the method comprising:
receiving, by the computing device, an input requesting generation of a preview segment from a base segment;
displaying, by the computing device in real time responsive to the input, a base accuracy/reach graph in a user interface, the displaying including:
generating base training data by sampling corresponding usage data from a base set of entities, defined by the base segment, taken from a plurality of entities included in a data lake;
training a base machine-learning model using the base training data;
generating search results, using the base machine-learning model, indicating event occurrence probabilities for the plurality of entities; and
generating the base accuracy/reach graph from the search results;
generating, by the computing device, the preview segment based on a user input specifying an amount of reach or accuracy via the base accuracy/reach graph; and
controlling, by the computing device, digital service operation of as part of an executable service platform of a service provider system based on a preview machine-learning model trained for the preview segment.