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11.
公开(公告)号:US20190034430A1
公开(公告)日:2019-01-31
申请号:US15663722
申请日:2017-07-29
Applicant: Splunk Inc.
Inventor: Dipock Das , Dayanand Pochugari , Neeraj Verma , Nikesh Padakanti , Aungon Nag Radon , Anand Srinivasabagavathar , Adam Oliner
Abstract: In various embodiments, a natural language (NL) application implements functionality that enables users to more effectively access various data storage systems based on NL requests. As described, the operations of the NL application are guided by, at least in part, on one or more templates and/or machine-learning models. Advantageously, the templates and/or machine-learning models provide a flexible framework that may be readily tailored to reduce the amount of time and user effort associated with processing NL requests and to increase the overall accuracy of NL application implementations.
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12.
公开(公告)号:US11170016B2
公开(公告)日:2021-11-09
申请号:US15663723
申请日:2017-07-29
Applicant: Splunk Inc.
Inventor: Dipock Das , Dayanand Pochugari , Neeraj Verma , Nikesh Padakanti , Aungon Nag Radon , Anand Srinivasabagavathar , Adam Oliner
IPC: G06F16/248 , G06N3/08 , G06F16/2452 , G06F16/242 , G06N20/10 , G06N5/02 , G06N5/04
Abstract: A natural language (NL) application implements functionality that enables users to more effectively access various data storage systems based on NL requests. The operations of the NL application are guided by, at least in part, on one or more templates and/or machine-learning models. Advantageously, the templates and/or machine-learning models provide a flexible framework that may be readily tailored to reduce the amount of time and user effort associated with processing NL requests and to increase the overall accuracy of NL application implementations.
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公开(公告)号:US10713269B2
公开(公告)日:2020-07-14
申请号:US15663721
申请日:2017-07-29
Applicant: Splunk Inc.
Inventor: Dipock Das , Dayanand Pochugari , Neeraj Verma , Nikesh Padakanti , Aungon Nag Radon , Anand Srinivasabagavathar , Adam Oliner
IPC: G06F16/00 , G06F16/248 , G06N3/08 , G06F16/242 , G06F16/2452 , G06N5/02 , G06N5/04 , G06N20/10
Abstract: In various embodiments, a natural language (NL) application implements functionality that enables users to more effectively access various data storage systems based on NL requests. As described, the operations of the NL application are guided by, at least in part, on one or more templates and/or machine-learning models. Advantageously, the templates and/or machine-learning models provide a flexible framework that may be readily tailored to reduce the amount of time and user effort associated with processing NL requests and to increase the overall accuracy of NL application implementations.
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14.
公开(公告)号:US20190034484A1
公开(公告)日:2019-01-31
申请号:US15663726
申请日:2017-07-29
Applicant: Splunk Inc.
Inventor: Dipock Das , Dayanand Pochugari , Neeraj Verma , Nikesh Padakanti , Aungon Nag Radon , Anand Srinivasabagavathar , Adam Oliner
CPC classification number: G06F16/24534 , G06F16/24522 , G06F16/248 , G06N3/08 , G06N5/022 , G06N5/046 , G06N20/00 , G06N20/10
Abstract: In various embodiments, a natural language (NL) application implements functionality that enables users to more effectively access various data storage systems based on NL requests. As described, the operations of the NL application are guided by, at least in part, on one or more templates and/or machine-learning models. Advantageously, the templates and/or machine-learning models provide a flexible framework that may be readily tailored to reduce the amount of time and user effort associated with processing NL requests and to increase the overall accuracy of NL application implementations.
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15.
公开(公告)号:US20190034429A1
公开(公告)日:2019-01-31
申请号:US15663720
申请日:2017-07-29
Applicant: Splunk Inc.
Inventor: Dipock Das , Dayanand Pochugari , Neeraj Verma , Nikesh Padakanti , Aungon Nag Radon , Anand Srinivasabagavathar , Adam Oliner
Abstract: In various embodiments, a natural language (NL) application implements functionality that enables users to more effectively access various data storage systems based on NL requests. As described, the operations of the NL application are guided by, at least in part, on one or more templates and/or machine-learning models. Advantageously, the templates and/or machine-learning models provide a flexible framework that may be readily tailored to reduce the amount of time and user effort associated with processing NL requests and to increase the overall accuracy of NL application implementations.
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