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公开(公告)号:US11907840B2
公开(公告)日:2024-02-20
申请号:US18061189
申请日:2022-12-02
Applicant: Verizon Patent and Licensing Inc.
Inventor: Sumit Singh , Balagangadhara Thilak Adiboina , Adithya Umakanth , Ganesh Narasimman , Sambasiva R Bhatta , Anurag Pant
IPC: G06Q30/016 , G06N3/08 , G06N3/044 , G06N3/045
CPC classification number: G06N3/08 , G06N3/044 , G06N3/045 , G06Q30/016
Abstract: A device may receive historical data and real-time data associated with a troubleshooting service, identify, using a machine learning model, an optimal resolution based on the historical data and the real-time data, and identify, using a graph analytics model, an optimal path of actions based on the optimal resolution. The machine learning model may be trained to identify one of the set of historical issues associated with the unresolved issue, and identify the optimal resolution based on one of the set of historical resolutions associated with the one of the set of historical issues. The graph analytics model may be trained to generate a set of paths of actions based on the historical data, and identify the optimal path based on respective numbers of actions associated with the set of paths. The device may identify optimal action based on the optimal path and the prior action.
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公开(公告)号:US11526751B2
公开(公告)日:2022-12-13
申请号:US16694891
申请日:2019-11-25
Applicant: Verizon Patent and Licensing Inc.
Inventor: Sumit Singh , Balagangadhara Thilak Adiboina , Adithya Umakanth , Ganesh Narasimman , Sambasiva R Bhatta , Anurag Pant
Abstract: A device may receive historical data and real-time data associated with a troubleshooting service, identify, using a machine learning model, an optimal resolution based on the historical data and the real-time data, and identify, using a graph analytics model, an optimal path of actions based on the optimal resolution. The machine learning model may be trained to identify one of the set of historical issues associated with the unresolved issue, and identify the optimal resolution based on one of the set of historical resolutions associated with the one of the set of historical issues. The graph analytics model may be trained to generate a set of paths of actions based on the historical data, and identify the optimal path based on respective numbers of actions associated with the set of paths. The device may identify optimal action based on the optimal path and the prior action.
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