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US-2018173698-A1 · Jun 21, 2018 · US
US2023283532A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2023283532-A1 |
| Application number | US-202217686169-A |
| Country | US |
| Kind code | A1 |
| Filing date | Mar 3, 2022 |
| Priority date | Mar 3, 2022 |
| Publication date | Sep 7, 2023 |
| Grant date | — |
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An organization has or uses an SLA system that selects a service-level agreement (SLA) that should apply to a given user request. The SLA system then can monitor the state of the ticket created based on the user request and provide messages or other feedback to the agent to aid the agent in meeting any performance goals associated with the SLA. The SLA system can determine the SLA to associate with a given user request by inferring a type of the request and selecting the SLA based on the type, or by using a model to directly associate an SLA to a given user request, without the need to infer an intermediate type for the user request, which eliminates the need for administrators to create and maintain metadata to guide the association between types and SLAs.
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1 . A computer-implemented method of assigning SLAs for responding to user requests, comprising: receiving a request from a user over a messaging system, the request containing text; providing at least the text, an identity of the user, a type of the request, and a time of the request, as input to a machine-learned model; selecting, using the machine-learned model, a service-level agreement (SLA) to apply to the request, the SLA having an associated goal; generating, for the request, a service ticket that is associated with the selected SLA; determining an agent to be assigned to the service ticket; monitoring handling of the service ticket to determine whether a deadline associated with the ticket is approaching; and responsive to determining that the deadline associated with the ticket is approaching, using the messaging system to provide a warning to the agent of potential breach. 2 . A computer-implemented method of assigning SLAs for responding to user requests, comprising: receiving a request from a user; based on at least an identity of the user and a type of the request, using a machine-learned model, selecting a service-level agreement (SLA) to apply to the request; and monitoring handling of the request to determine whether the SLA is being met. 3 . The computer-implemented method of claim 2 , wherein the SLA has a goal including a metric type and a value for the metric. 4 . The computer-implemented method of claim 2 , wherein the SLA an applicability condition that determines whether the SLA is applicable to the request. 5 . The computer-implemented method of claim 2 , wherein the SLA is selected to apply to the request by providing at least the identity of the user and the type of the request as input to a machine-learned model that identifies an applicable SLA. 6 . The computer-implemented method of claim 5 , further comprising: presenting the selected SLA in a graphical user interface to an agent handling the request; noting that the agent selected an SLA different from the selected SLA for the request; including the different SLA in a training set; and retraining the machine-learned model using the training set. 7 . The computer-implemented method of claim 2 , wherein the SLA is selected based on a predetermined mapping of request types to SLAs. 8 . The computer-implemented method of claim 2 , further comprising determining the type of the request by applying a machine-learned model to text associated with the request. 9 . The computer-implemented method of claim 2 , wherein the request from the user is specified in a textual message sent via a messaging system. 10 . A computer system comprising: a computer processor; and a non-transitory computer-readable storage medium storing instructions that when executed by the computer processor perform actions comprising: receiving a request from a user; based on at least an identity of the user and a type of the request, using a machine-learned model, selecting a service-level agreement (SLA) to apply to the request; and monitoring handling of the request to determine whether the SLA is being met. 11 . The computer system of claim 10 , wherein the SLA has a goal including a metric type and a value for the metric. 12 . The computer system of claim 10 , wherein the SLA an applicability condition that determines whether the SLA is applicable to the request. 13 . The computer system of claim 10 , wherein the SLA is selected to apply to the request by providing at least the identity of the user and the type of the request as input to a machine-learned model that identifies an applicable SLA. 14 . The computer system of claim 13 , the actions further comprising: presenting the selected SLA in a graphical user interface to an agent handling the request; noting that the agent selected an SLA different from the selected SLA for the request; including the different SLA in a training set; and retraining the machine-learned model using the training set. 15 . The computer system of claim 10 , wherein the SLA is selected based on a predetermined mapping of request types to SLAs. 16 . The computer system of claim 10 , the actions further comprising determining the type of the request by applying a machine-learned model to text associated with the request. 17 . The computer system of claim 10 , wherein the request from the user is specified in a textual message sent via a messaging system.
involving simulating, designing, planning or modelling of a network · CPC title
Handling of user complaints or trouble tickets · CPC title
Service discovery by the service manager · CPC title
comprising specially adapted graphical user interfaces [GUI] · CPC title
characterised by the time relationship between creation and deployment of a service · CPC title
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