US 11,722,380 B2
Utilizing machine learning models to determine customer care actions for telecommunications network providers
Thomas Fiumara, Milan (IT); Marta Castrigno, Milan (IT); Luigi Tripputi, Milan (IT); Marco Grigoletti, Milan (IT); and Jessica Gobetti, Canegrate (IT)
Assigned to Accenture Global Solutions Limited, Dublin (IE)
Filed by Accenture Global Solutions Limited, Dublin (IE)
Filed on Nov. 10, 2020, as Appl. No. 17/94,664.
Prior Publication US 2022/0150132 A1, May 12, 2022
Int. Cl. H04L 41/16 (2022.01); H04L 41/5067 (2022.01); G06N 20/00 (2019.01); H04L 43/062 (2022.01); G06F 21/62 (2013.01); G06F 18/214 (2023.01)
CPC H04L 41/16 (2013.01) [G06F 18/214 (2023.01); G06F 21/6254 (2013.01); G06N 20/00 (2019.01); H04L 41/5067 (2013.01); H04L 43/062 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method, comprising:
receiving, by a device and from a monitoring device, anonymized historical telecommunications data associated with a telecommunications network that is monitored with the monitoring device,
wherein the monitoring device is a separate device from the device,
wherein the monitoring device is configured to perform a set of test logins using a set of usernames and passwords,
wherein the set of usernames and passwords is anonymized to create the anonymized historical telecommunications data,
wherein the monitoring device is configured to determine a customer care action to resolve a technical issue with the telecommunications network, and
wherein the monitoring device is configured to cause the customer care action to be implemented in the telecommunications network;
training, by the device, a plurality of machine learning models with the anonymized historical telecommunications data to generate a plurality of trained machine learning models;
generating, by the device, accuracy scores for the plurality of trained machine learning models based on training the plurality of machine learning models;
selecting, by the device, an optimum machine learning model, from the plurality of trained machine learning models, based on the accuracy scores for the plurality of trained machine learning models; and
providing, by the device, the optimum machine learning model to the monitoring device associated with the telecommunications network,
wherein the optimum machine learning model causes the monitoring device to:
process real time telecommunications data of the telecommunications network, with the optimum machine learning model, to determine the customer care action for the telecommunications network, and
cause the customer care action to be applied to an end customer utilizing a service provided by a telecommunications provider associated with the telecommunications network.