US 12,010,075 B2
Utilizing machine learning models to generate interactive digital text threads with personalized digital text reply options
Jigar Mehta, Milpitas, CA (US); Abbey Chaver, Berkley, CA (US); Abhi Sharma, San Francisco, CA (US); and Sashidhar Guntury, Los Angeles, CA (US)
Assigned to Chime Financial, Inc., San Francisco, CA (US)
Filed by Chime Financial, Inc., San Francisco, CA (US)
Filed on Jun. 29, 2022, as Appl. No. 17/809,765.
Prior Publication US 2024/0007421 A1, Jan. 4, 2024
Int. Cl. H04L 51/02 (2022.01); G06F 16/35 (2019.01); H04L 51/046 (2022.01)
CPC H04L 51/02 (2013.01) [G06F 16/355 (2019.01); H04L 51/046 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
extracting client features corresponding to a client device participating in an automated interactive digital text thread;
identifying a hierarchical intent architecture comprising a plurality of intent classifications organized in a plurality of hierarchical layers;
generating, from the hierarchical intent architecture utilizing a machine learning model, a plurality of predicted client intent classifications and a plurality of intent classification probabilities from the client features;
applying a bonus weight to a first intent classification probability of the plurality of intent classification probabilities associated with a first predicted client intent classification from a first hierarchical layer of the plurality of hierarchical layers, the bonus weight based on the first hierarchical layer;
selecting the first predicted client intent classification and at least two one additional predicted client intent classification from the plurality of predicted client intent classifications utilizing the plurality of intent classification probabilities; and
providing, for display via the client device, at least two personalized digital text reply options corresponding to the first predicted client intent classification and the at least two one additional predicted client intent classification via the automated interactive digital text thread.