US 12,321,942 B2
System, method, and computer program product for predicting a specified geographic area of a user
Mahashweta Das, Campbell, CA (US); and Hao Yang, San Jose, CA (US)
Assigned to Visa International Service Association, San Francisco, CA (US)
Filed by Visa International Service Association, San Francisco, CA (US)
Filed on Jul. 16, 2024, as Appl. No. 18/773,655.
Application 18/773,655 is a continuation of application No. 16/971,798, granted, now 12,067,570, previously published as PCT/US2018/019308, filed on Feb. 23, 2018.
Prior Publication US 2024/0370871 A1, Nov. 7, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06Q 20/40 (2012.01); G06N 20/00 (2019.01); G06Q 30/0211 (2023.01); H04W 4/029 (2018.01)
CPC G06Q 20/4015 (2020.05) [G06N 20/00 (2019.01); G06Q 20/4093 (2013.01); G06Q 30/0211 (2013.01); H04W 4/029 (2018.02)] 20 Claims
OG exemplary drawing
 
1. A system comprising:
at least one processor configured to:
determine, for each user of a plurality of users, a verified geographic area associated with the user;
determine, for each user of the plurality of users, a feature vector associated with an account of the user, each parameter of the feature vector associated with a value based on a maximum number of transactions conducted by the user with the account in a geographic area of a plurality of geographic areas;
receive transaction data associated with a plurality of transactions involving each user of the plurality of users;
determine a value of each parameter of the feature vector for each user of the plurality of users based on the transaction data to produce a training matrix, wherein each row of the training matrix comprises values of a feature vector associated with a user of the plurality of users;
train a geographic area prediction model based on the training matrix;
validate the geographic area prediction model based on the training matrix;
repeatedly generate a prediction that a user will conduct a transaction in a geographic area based on the geographic area prediction model;
repeatedly communicate an offer to the user based on the prediction;
repeatedly receive new training data by processing a transaction conducted by the user in the geographic area within a predetermined amount of time from the offer being communicated to the user; and
repeatedly update the geographic area prediction model based on the new training data.