US 12,112,277 B2
Computer-based systems configured to utilize predictive machine learning techniques to define software objects and methods of use thereof
Venkatesh Nagarajan, Scottsdale, AZ (US); Xiangzhen Kong, Hoboken, NJ (US); Neha Arya, New York, NY (US); and Mansi Sharma, Edison, NJ (US)
Assigned to American Express Travel Related Services Company, Inc., New York, NY (US)
Filed by American Express Travel Related Services Company, Inc., New York, NY (US)
Filed on Feb. 16, 2023, as Appl. No. 18/110,561.
Application 18/110,561 is a continuation of application No. 16/731,991, filed on Dec. 31, 2019, granted, now 11,593,677.
Prior Publication US 2023/0196143 A1, Jun. 22, 2023
Int. Cl. G06F 7/00 (2006.01); G06F 16/9535 (2019.01); G06N 5/04 (2023.01); G06N 20/00 (2019.01)
CPC G06N 5/04 (2013.01) [G06F 16/9535 (2019.01); G06N 20/00 (2019.01)] 18 Claims
OG exemplary drawing
 
1. A system, comprising:
a processor; and
a non-transitory memory storing instructions which, when executed by the processor, causes the processor to:
receive a user activity profile of a user;
determine, using a categorization machine learning model, a first aspect of a user profile based on at least the user activity profile;
determine, using a risk assessment model, a second aspect of the user profile based on at least the user activity profile;
predict, using a trained optimization machine learning model, a set of software objects based on the first aspect and the second aspect, wherein a software object of the set of software objects is optimized with respect to at least one competitive interest between the user and an entity provider of the software object, and wherein the software object is associated with feature values; and
output a notification indicative of the set of software objects and corresponding feature values to a computing device associated with the user, wherein the set of software objects and the corresponding features values are displayed on a user interface of the computing device associated with the user.