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公开(公告)号:US11416823B2
公开(公告)日:2022-08-16
申请号:US16451485
申请日:2019-06-25
Applicant: KYNDRYL, INC.
Inventor: Nikhil Malhotra , Atri Mandal , Giriprasad Sridhara , Vijay Ekambaram
IPC: G06Q30/00 , G06N99/00 , G06F11/07 , G06Q10/06 , G06F3/0482 , G06Q10/10 , G06F40/30 , G06F40/205
Abstract: A help desk management system uses segment partitioning and matching of each identified segment to a suitable problem and resolver group and then sequencing the partitioned segments based on sentiment analysis and sequence mining on historical tickets and audit logs to actuate effective resolution and pipelining of helpdesk tickets needing resolutions from multiple resolver groups. The helpdesk tickets can be in the form of e-mails.
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公开(公告)号:US20230222391A1
公开(公告)日:2023-07-13
申请号:US18184938
申请日:2023-03-16
Applicant: KYNDRYL, INC.
Inventor: Nikhil Malhotra , Atri Mandal , Giriprasad Sridhara , Vijay Ekambaram
Abstract: A cognitive assignment engine (CAE) system attempts to infer semantic meaning from textual content of an incoming message in order to use the inferred meaning to assign the message to an appropriate responder. If the message contains insufficient textual content, the system identifies ontological structures comprised by the message's graphical content and classifies each structure as a function of the structure's location within the graphical content or of an intrinsic characteristic of the structure. The system then generates a message identifier by performing a computation on these classifications and uses the identifier to retrieve a previously stored graphical template that comprises ontological structures similar to those of the incoming message. The system associates the incoming message with a semantic meaning previously associated with the template, enabling the system to classify the message and to assign the message to the correct responder.
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公开(公告)号:US11620570B2
公开(公告)日:2023-04-04
申请号:US16449906
申请日:2019-06-24
Applicant: KYNDRYL, INC.
Inventor: Nikhil Malhotra , Atri Mandal , Giriprasad Sridhara , Vijay Ekambaram
Abstract: A cognitive assignment engine (CAE) system attempts to infer semantic meaning from textual content of an incoming message in order to use the inferred meaning to assign the message to an appropriate responder. If the message contains insufficient textual content, the system identifies ontological structures comprised by the message's graphical content and classifies each structure as a function of the structure's location within the graphical content or of an intrinsic characteristic of the structure. The system then generates a message identifier by performing a computation on these classifications and uses the identifier to retrieve a previously stored graphical template that comprises ontological structures similar to those of the incoming message. The system associates the incoming message with a semantic meaning previously associated with the template, enabling the system to classify the message and to assign the message to the correct responder.
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