公开(公告)号：US20200183930A1

公开(公告)日：2020-06-11

申请号：US16790554

申请日：2020-02-13

Applicant: Splunk Inc.

Inventor： Dipock Das ,  Dayanand Pochugari ,  Neeraj Verma ,  Nikesh Padakanti ,  Aungon Nag Radon ,  Anand Srinivasabagavathar ,  Adam Oliner

IPC: G06F16/2453 ,  G06F16/2452 ,  G06F16/248 ,  G06N20/00 ,  G06N20/10 ,  G06N5/02 ,  G06N3/08 ,  G06N5/04

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.

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

IPC: G06F17/30 ,  G06N99/00 ,  G06N5/04

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.

公开(公告)号：US12189644B1

公开(公告)日：2025-01-07

申请号：US17975249

申请日：2022-10-27

Applicant: SPLUNK INC.

Inventor： Dipock Das ,  Dayanand Pochugari ,  Aungon Nag Radon ,  Adam Oliner ,  Nikesh Padakanti ,  Roussi Roussev

IPC: G06F16/248 ,  G06F16/242 ,  G06F16/2452 ,  G06N5/022 ,  G06N5/046

Abstract: In various embodiments, a natural language (NL) application enables users to more effectively access various data storage systems based on NL requests. The NL application includes functionality for selecting an optimal interpretation algorithm, generating a dashboard, and/or generating an alert based on an NL request. Advantageously, the operations performed by the NL application reduce the amount of time and user effort associated with accessing data storage systems and increase the likelihood of properly addressing NL requests.

公开(公告)号：US11288319B1

公开(公告)日：2022-03-29

申请号：US16147435

申请日：2018-09-28

Applicant: Splunk Inc.

Inventor： Dipock Das ,  Dayanand Pochugari ,  Aungon Nag Radon

IPC: G06F40/30 ,  G06F16/9032 ,  G06N20/00

Abstract: In various embodiments, a natural language (NL) application implements functionality for recommending trending NL requests to users of the application. The functionality includes generating rating data associated with a plurality of natural language (NL) requests and one or more intents corresponding to the plurality of NL requests, wherein the rating data indicates a preference of at least one user for using at least one of the plurality of NL request to access data, training a trends recommendation model based on the rating data associated with the plurality of NL requests, generating a set of NL request recommendations based on the trends recommendation model, and causing the set of NL request recommendations to be presented in a query recommendation interface.

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.

公开(公告)号：US11017764B1

公开(公告)日：2021-05-25

申请号：US16147426

申请日：2018-09-28

Applicant: Splunk Inc.

Inventor： Dipock Das ,  Dayanand Pochugari ,  Aungon Nag Radon

IPC: G10L15/18 ,  G06F16/242 ,  G06N20/00 ,  G06F16/2457 ,  G10L15/22 ,  G06F16/903

Abstract: In various embodiments, a natural language (NL) application receives a partial NL request associated with a first context, and determining that the partial NL request corresponds to at least a portion of a first next NL request prediction included in one or more next NL request predictions generated based on a first natural language (NL) request, the first context associated with the first NL request, and a first sequence prediction model, where the first sequence prediction model is generated via a machine learning algorithm applied to a first data dependency model and a first request prediction model. In response to determining that the partial NL request corresponds to at least the portion of the first next NL request prediction, the NL application generates a complete NL request based on the first NL request and the partial NL request, and causes the complete NL request to be applied to a data storage system.

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.

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

IPC: G06F17/30 ,  G06N99/00

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.

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

IPC: G06F17/30 ,  G06F17/27 ,  G06F17/24 ,  G06N5/04

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.