US 11,734,738 B2
Method, device, and medium for utilizing machine learning and transaction data to match boycotts of merchants to customers
Michael Mossoba, Great Falls, VA (US); Abdelkadar M'Hamed Benkreira, Washington, DC (US); and Joshua Edwards, Philadelphia, PA (US)
Assigned to Capital One Services, LLC, McLean, VA (US)
Filed by Capital One Services, LLC, McLean, VA (US)
Filed on Jun. 2, 2022, as Appl. No. 17/805,063.
Application 17/805,063 is a continuation of application No. 16/828,097, filed on Mar. 24, 2020, granted, now 11,361,352.
Application 16/828,097 is a continuation of application No. 16/425,116, filed on May 29, 2019, granted, now 10,636,068, issued on Apr. 28, 2020.
Prior Publication US 2022/0292558 A1, Sep. 15, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06Q 30/00 (2023.01); G06Q 30/0601 (2023.01)
CPC G06Q 30/0609 (2013.01) [G06Q 30/0617 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method, comprising:
receiving, by a device, user preference data;
processing, by the device, third-party boycott data and the user preference data, with a machine learning model trained using a particular feature set, to identify a boycott that is predicted to be of interest to a user,
wherein the particular feature set is generated based at least in part on performing dimensionality reduction of historical third-party boycott data and historical user preference data, and
wherein the machine learning model applies a classification technique to the particular feature set to determine an output to associate boycotts to users that are predicted to have an interest in the boycott;
determining, by the device, that the user desires to join the boycott; and
performing, by the device, one or more actions based on determining that the user desires to join the boycott.