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公开(公告)号：US11960575B1
公开(公告)日：2024-04-16
申请号：US17975122
申请日：2022-10-27
Applicant: Splunk Inc.
Inventor： Manish Sainani , Sergey Slepian , Di Lu , Adam Oliner , Jacob Leverich , Iryna Vogler-Ivashchanka , Iman Makaremi
IPC: G06F7/00 , G06F16/2458 , G06F18/21 , G06F18/25 , G06F18/40 , G06N5/025 , G06N20/00 , G06V10/94 , G06V40/12 , G06F9/455
CPC classification number: G06F18/251 , G06F16/2465 , G06F18/217 , G06F18/40 , G06N5/025 , G06N20/00 , G06V10/95 , G06V40/1347 , G06F9/455 , G06F2216/03
Abstract: Embodiments of the present invention are directed to facilitating data preprocessing for machine learning. In accordance with aspects of the present disclosure, a training set of data is accessed. A preprocessing query specifying a set of preprocessing parameter values that indicate a manner in which to preprocess the training set of data is received. Based on the preprocessing query, a preprocessing operation is performed to preprocess the training set of data in accordance with the set of preprocessing parameter values to obtain a set of preprocessed data. The set of preprocessed data can be provided for presentation as a preview. Based on an acceptance of the set of preprocessed data, the set of preprocessed data is used to train a machine learning model that can be subsequently used to predict data.
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公开(公告)号：US20190034767A1
公开(公告)日：2019-01-31
申请号：US15665224
申请日：2017-07-31
Applicant: Splunk Inc.
Inventor： Manish Sainani , Sergey Slepian , Di Lu , Adam Oliner , Jacob Leverich , Iryna Vogler-Ivashchanka , Iman Makaremi
CPC classification number: G06K9/6289 , G06F9/455 , G06F16/2465 , G06F2216/03 , G06K9/00067 , G06K9/00979 , G06K9/6253 , G06K9/6262 , G06N5/025 , G06N20/00
Abstract: Embodiments of the present invention are directed to facilitating data preprocessing for machine learning. In accordance with aspects of the present disclosure, a training set of data is accessed. A preprocessing query specifying a set of preprocessing parameter values that indicate a manner in which to preprocess the training set of data is received. Based on the preprocessing query, a preprocessing operation is performed to preprocess the training set of data in accordance with the set of preprocessing parameter values to obtain a set of preprocessed data. The set of preprocessed data can be provided for presentation as a preview. Based on an acceptance of the set of preprocessed data, the set of preprocessed data is used to train a machine learning model that can be subsequently used to predict data.
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公开(公告)号：US12198021B2
公开(公告)日：2025-01-14
申请号：US17190751
申请日：2021-03-03
Applicant: Splunk Inc.
Inventor： Manish Sainani , Sergey Slepian , Iman Makaremi , Adam Jamison Oliner , Jacob Leverich , Di Lu
Abstract: Disclosed herein is a computer-implemented tool that facilitates data analysis by use of machine learning (ML) techniques. The tool cooperates with a data intake and query system and provides a graphical user interface (GUI) that enables a user to train and apply a variety of different ML models on user-selected datasets of stored machine data. The tool can provide active guidance to the user, to help the user choose data analysis paths that are likely to produce useful results and to avoid data analysis paths that are less likely to produce useful results.
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公开(公告)号：US20210192395A1
公开(公告)日：2021-06-24
申请号：US17190751
申请日：2021-03-03
Applicant: Splunk Inc.
Inventor： Manish Sainani , Sergey Slepian , Iman Makaremi , Adam Jamison Oliner , Jacob Leverich , Di Lu
Abstract: Disclosed herein is a computer-implemented tool that facilitates data analysis by use of machine learning (ML) techniques. The tool cooperates with a data intake and query system and provides a graphical user interface (GUI) that enables a user to train and apply a variety of different ML models on user-selected datasets of stored machine data. The tool can provide active guidance to the user, to help the user choose data analysis paths that are likely to produce useful results and to avoid data analysis paths that are less likely to produce useful results.
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公开(公告)号：US20210004651A1
公开(公告)日：2021-01-07
申请号：US17029365
申请日：2020-09-23
Applicant: SPLUNK INC.
Inventor： Manish Sainani , Sergey Slepian , Di Lu , Adam Oliner , Jacob Leverich , Iryna Vogler-Ivashchanka , Iman Makaremi
IPC: G06K9/62 , G06K9/00 , G06N20/00 , G06F16/2458 , G06N5/02
Abstract: Embodiments of the present invention are directed to facilitating data preprocessing for machine learning. In accordance with aspects of the present disclosure, a training set of data is accessed. A preprocessing query specifying a set of preprocessing parameter values that indicate a manner in which to preprocess the training set of data is received. Based on the preprocessing query, a preprocessing operation is performed to preprocess the training set of data in accordance with the set of preprocessing parameter values to obtain a set of preprocessed data. The set of preprocessed data can be provided for presentation as a preview. Based on an acceptance of the set of preprocessed data, the set of preprocessed data is used to train a machine learning model that can be subsequently used to predict data.
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Patent Agency Ranking
公开(公告)号：US10817757B2
公开(公告)日：2020-10-27
申请号：US15665224
申请日：2017-07-31
Applicant: Splunk Inc.
Inventor： Manish Sainani , Sergey Slepian , Di Lu , Adam Oliner , Jacob Leverich , Iryna Vogler-Ivashchanka , Iman Makaremi
Abstract: Embodiments of the present invention are directed to facilitating data preprocessing for machine learning. In accordance with aspects of the present disclosure, a training set of data is accessed. A preprocessing query specifying a set of preprocessing parameter values that indicate a manner in which to preprocess the training set of data is received. Based on the preprocessing query, a preprocessing operation is performed to preprocess the training set of data in accordance with the set of preprocessing parameter values to obtain a set of preprocessed data. The set of preprocessed data can be provided for presentation as a preview. Based on an acceptance of the set of preprocessed data, the set of preprocessed data is used to train a machine learning model that can be subsequently used to predict data.
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公开(公告)号：US10607150B2
公开(公告)日：2020-03-31
申请号：US15050785
申请日：2016-02-23
Applicant: Splunk Inc.
Inventor： Manish Sainani , Sergey Slepian , Iman Makaremi , Adam Jamison Oliner , Jacob Leverich , Di Lu
Abstract: Disclosed herein is a computer-implemented tool that facilitates data analysis by use of machine learning (ML) techniques. The tool cooperates with a data intake and query system and provides a graphical user interface (GUI) that enables a user to train and apply a variety of different ML models on user-selected datasets of stored machine data. The tool can provide active guidance to the user, to help the user choose data analysis paths that are likely to produce useful results and to avoid data analysis paths that are less likely to produce useful results.
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公开(公告)号：US20180218285A1
公开(公告)日：2018-08-02
申请号：US15420618
申请日：2017-01-31
Applicant: SPLUNK INC.
Inventor： Adam Jamison Oliner , Hongyang Zhang , Sergey Slepian , Di Lu , XiaoYu Jia , Peter Chongjin Kim , Manish Sainani
CPC classification number: G06N20/00 , G06F16/2457 , G06N5/04
Abstract: Embodiments of the present invention are directed to facilitating search input recommendations. In accordance with aspects of the present disclosure, a set of events determined from raw machine data is obtained. The events are analyzed to generate a temporal map associated with the set of events. Generally, the temporal map associates candidate terms with temporally related terms that occur within a period of time corresponding with the candidate terms. A search term input into a search field is received. Based on the input search term, the temporal map is used to identify one or more temporally related term recommendations.
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公开(公告)号：US11514278B2
公开(公告)日：2022-11-29
申请号：US17029365
申请日：2020-09-23
Applicant: SPLUNK INC.
Inventor： Manish Sainani , Sergey Slepian , Di Lu , Adam Oliner , Jacob Leverich , Iryna Vogler-Ivashchanka , Iman Makaremi
Abstract: Embodiments of the present invention are directed to facilitating data preprocessing for machine learning. In accordance with aspects of the present disclosure, a training set of data is accessed. A preprocessing query specifying a set of preprocessing parameter values that indicate a manner in which to preprocess the training set of data is received. Based on the preprocessing query, a preprocessing operation is performed to preprocess the training set of data in accordance with the set of preprocessing parameter values to obtain a set of preprocessed data. The set of preprocessed data can be provided for presentation as a preview. Based on an acceptance of the set of preprocessed data, the set of preprocessed data is used to train a machine learning model that can be subsequently used to predict data.
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公开(公告)号：US11194794B2
公开(公告)日：2021-12-07
申请号：US15420618
申请日：2017-01-31
Applicant: SPLUNK INC.
Inventor： Adam Jamison Oliner , Hongyang Zhang , Sergey Slepian , Di Lu , XiaoYu Jia , Peter Chongjin Kim , Manish Sainani
IPC: G06F16/242 , G06N5/04 , G06N20/00 , G06F16/2457 , G06F16/2458
Abstract: Embodiments of the present invention are directed to facilitating search input recommendations. In accordance with aspects of the present disclosure, a set of events determined from raw machine data is obtained. The events are analyzed to generate a temporal map associated with the set of events. Generally, the temporal map associates candidate terms with temporally related terms that occur within a period of time corresponding with the candidate terms. A search term input into a search field is received. Based on the input search term, the temporal map is used to identify one or more temporally related term recommendations.
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