US 11,710,033 B2
Unsupervised machine learning system to automate functions on a graph structure
Ronnie J. Morris, Mesquite, TX (US); Dana M. Pusey-Conlin, Wilmington, DE (US); Lorraine C. Edkin, Jacksonville, FL (US); Scott A. Sims, Tega Cay, SC (US); Joel Filliben, Newark, DE (US); Margaret A. Payne, Elkton, MD (US); Craig Douglas Widmann, Chandler, AZ (US); and Eren Kursun, New York, NY (US)
Assigned to Bank of America Corporation, Charlotte, NC (US)
Filed by Bank of America Corporation, Charlotte, NC (US)
Filed on Jun. 12, 2018, as Appl. No. 16/6,559.
Prior Publication US 2019/0378010 A1, Dec. 12, 2019
Int. Cl. G06N 3/08 (2023.01); G06N 3/04 (2023.01); G06F 16/26 (2019.01); G06F 16/28 (2019.01); G06F 16/22 (2019.01)
CPC G06N 3/08 (2013.01) [G06F 16/2291 (2019.01); G06F 16/26 (2019.01); G06F 16/288 (2019.01); G06N 3/04 (2013.01)] 14 Claims
OG exemplary drawing
 
1. A method comprising:
determining data corresponding to one or more graph representations of a first plurality of entities, wherein the one or more graph representations indicate a plurality of relationships between at least two of the first plurality of entities, and wherein the one or more graph representations are unlabeled;
training, using the data corresponding to the one or more graph representations, an artificial neural network for machine learning executing on one or more computing devices, wherein the artificial neural network comprises a plurality of nodes, wherein the nodes are configured to process an input, and wherein the plurality of nodes are configured based on the one or more graph representations;
determining a first graph representation comprising a second plurality of entities;
determining a plurality of definitional functions corresponding to one or more of the second plurality of entities;
receiving, from the artificial neural network and based on the first graph representation and the plurality of definitional functions, output indicating a modification to a hotfile; and
modifying the hotfile associated with one or more entities of the first plurality of entities, wherein the hotfile is a dynamic graph representing risk associated with transaction data.