公开(公告)号：US20240177173A1

公开(公告)日：2024-05-30

申请号：US18429584

申请日：2024-02-01

Applicant: AT&T Intellectual Property I, L.P.

Inventor： James Fan ,  Al Hooshiari ,  Dan Celenti ,  Eric Forbes

IPC: G06Q30/016 ,  G06N5/01 ,  G06N20/00 ,  G06Q10/0631 ,  G06Q10/0633

CPC classification number: G06Q30/016 ,  G06N5/01 ,  G06N20/00 ,  G06Q10/06315 ,  G06Q10/0633

Abstract: Concepts and technologies disclosed herein are directed to interpretation workflows for machine learning-enabled event tree-based diagnostic and customer problem resolution. According to one aspect, a system can receive a workflow construction specification derived from a machine learning-enabled event tree (“MLET”). The MLET can be generated for use by a customer service agent to resolve a customer problem. The workflow construction specification can include a plurality of objects, each of which represents a navigation path through the MLET. The system can traverse the workflow construction specification and can create a set of workflow creation commands based upon at least one policy. The system can generate a workflow visualization interpretation file based upon the set of workflow creation commands. The workflow visualization interpretation file can identify how the MLET derived a root cause of the customer problem. The system can then present the workflow visualization interpretation file to the customer service agent.

公开(公告)号：US12299695B2

公开(公告)日：2025-05-13

申请号：US18429584

申请日：2024-02-01

Applicant: AT&T Intellectual Property I, L.P.

Inventor： James Fan ,  Al Hooshiari ,  Dan Celenti ,  Eric Forbes

IPC: G06Q10/00 ,  G06N5/01 ,  G06N20/00 ,  G06Q10/0631 ,  G06Q10/0633 ,  G06Q30/016

Abstract: Concepts and technologies disclosed herein are directed to interpretation workflows for machine learning-enabled event tree-based diagnostic and customer problem resolution. According to one aspect, a system can receive a workflow construction specification derived from a machine learning-enabled event tree (“MLET”). The MLET can be generated for use by a customer service agent to resolve a customer problem. The workflow construction specification can include a plurality of objects, each of which represents a navigation path through the MLET. The system can traverse the workflow construction specification and can create a set of workflow creation commands based upon at least one policy. The system can generate a workflow visualization interpretation file based upon the set of workflow creation commands. The workflow visualization interpretation file can identify how the MLET derived a root cause of the customer problem. The system can then present the workflow visualization interpretation file to the customer service agent.

公开(公告)号：US11893590B2

公开(公告)日：2024-02-06

申请号：US17336396

申请日：2021-06-02

Applicant: AT&T Intellectual Property I, L.P.

Inventor： James Fan ,  Al Hooshiari ,  Dan Celenti ,  Eric Forbes

IPC: G06Q10/00 ,  G06Q30/016 ,  G06Q10/0631 ,  G06N20/00 ,  G06Q10/0633 ,  G06N5/01

CPC classification number: G06Q30/016 ,  G06N5/01 ,  G06N20/00 ,  G06Q10/0633 ,  G06Q10/06315

Abstract: Concepts and technologies disclosed herein are directed to interpretation workflows for machine learning-enabled event tree-based diagnostic and customer problem resolution. According to one aspect, a system can receive a workflow construction specification derived from a machine learning-enabled event tree (“MLET”). The MLET can be generated for use by a customer service agent to resolve a customer problem. The workflow construction specification can include a plurality of objects, each of which represents a navigation path through the MLET. The system can traverse the workflow construction specification and can create a set of workflow creation commands based upon at least one policy. The system can generate a workflow visualization interpretation file based upon the set of workflow creation commands. The workflow visualization interpretation file can identify how the MLET derived a root cause of the customer problem. The system can then present the workflow visualization interpretation file to the customer service agent.

公开(公告)号：US20220391917A1

公开(公告)日：2022-12-08

申请号：US17336396

申请日：2021-06-02

Applicant: AT&T Intellectual Property I, L.P.

Inventor： James Fan ,  Al Hooshiari ,  Dan Celenti ,  Eric Forbes

IPC: G06Q30/00 ,  G06Q10/06 ,  G06N5/00 ,  G06N20/00

Abstract: Concepts and technologies disclosed herein are directed to interpretation workflows for machine learning-enabled event tree-based diagnostic and customer problem resolution. According to one aspect, a system can receive a workflow construction specification derived from a machine learning-enabled event tree (“MLET”). The MLET can be generated for use by a customer service agent to resolve a customer problem. The workflow construction specification can include a plurality of objects, each of which represents a navigation path through the MLET. The system can traverse the workflow construction specification and can create a set of workflow creation commands based upon at least one policy. The system can generate a workflow visualization interpretation file based upon the set of workflow creation commands. The workflow visualization interpretation file can identify how the MLET derived a root cause of the customer problem. The system can then present the workflow visualization interpretation file to the customer service agent.