US 12,033,222 B1
Demand prediction based on user input valuation
Chandrasekaran Sivaraman, Bangalore (IN); Priya R. Radia, Bangalore (IN); Ashalatha Seetharam, Bangalore (IN); Susmita Santra, Bangalore (IN); Manas Ranjan Sahu, Bangaluru (IN); Mothi Mai Malli Viswanathan, Bangalore (IN); Rajesh P. Mannachery, Bangaluru (IN); and Shanmukeswara Rao Donkada, Hyderabad (IN)
Assigned to Wells Fargo Bank, N.A., San Francisco, CA (US)
Filed by Wells Fargo Bank, N.A., San Francisco, CA (US)
Filed on Mar. 11, 2021, as Appl. No. 17/199,102.
Int. Cl. G06Q 40/00 (2023.01); G06F 16/28 (2019.01); G06N 20/00 (2019.01); G06Q 30/0282 (2023.01); G06Q 40/02 (2023.01); G06Q 50/00 (2012.01)
CPC G06Q 50/01 (2013.01) [G06F 16/285 (2019.01); G06N 20/00 (2019.01); G06Q 30/0282 (2013.01); G06Q 40/02 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system, comprising:
a processor coupled to a memory that includes instructions, that when executed by the processor, cause the processor to:
determine, by a score component, a first score associated with a user input regarding a first purchase posted in an electronic social network by a user, wherein the first score reflects a degree of agreement with the user input based on feedback to the user input posted in the electronic social network by other users;
train, by a training component, a model using training data comprising a set of scores that satisfy a predetermined threshold to determine recommendations for products or services, wherein the set of scores comprises the first score;
determine, by a recommendation component and using the model, a first recommendation for the user based on a user profile of the user and the first score;
convey, for display on a device and via a communication connection, the first recommendation in the electronic social network;
facilitate, by a profile component, a transaction for a product associated with the recommendation via the electronic social network; and
modify, by the profile component, a purchase history of the user profile based on the transaction.