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公开(公告)号：US11093837B2
公开(公告)日：2021-08-17
申请号：US15419918
申请日：2017-01-30
Applicant: SPLUNK INC.
Inventor： Adam Jamison Oliner , Aungon Nag Radon , Manwah Wong , Manish Sainani , Harsh Keswani
IPC: G06N5/04 , G06N20/00 , G06F16/2458 , G06F16/26
Abstract: Embodiments of the present invention are directed to facilitating event forecasting. In accordance with aspects of the present disclosure, a set of events determined from raw machine data is obtained. The events are analyzed to identify leading indicators that indicate a future occurrence of a target event, wherein the leading indicators occur during a search period of time the precedes a warning period of time, thereby providing time for an action to be performed prior to an occurrence of a predicted target event. At least one of the leading indicators is used to predict a target event. An event notification is provided indicating the prediction of the target event.
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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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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：US10776719B2
公开(公告)日：2020-09-15
申请号：US16244817
申请日：2019-01-10
Applicant: Splunk Inc.
Inventor： Sonal Maheshwari , Manish Sainani , Leonid Alekseyev , Alan Hardin , Jacob Barton Leverich , Adam Jamison Oliner , Brian Reyes , Alok Anant Bhide
Abstract: Techniques are disclosed for providing adaptive thresholding technology for Key Performance Indicators (KPIs) that are updated using training data. Adaptive thresholding technology may automatically assign new values or adjust existing values for one or more thresholds of one or more time policies. Assigning threshold values using adaptive thresholding may involve identifying training data (e.g., historical data, simulated data, or example data) for the time frames and analyzing the training data to identify variations within the data (e.g., patterns, distributions, trends). A threshold value may be determined based on the variations and may be assigned to one or more of the thresholds without additional user intervention.
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Patent Agency Ranking
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：US20170220672A1
公开(公告)日：2017-08-03
申请号：US15010732
申请日：2016-01-29
Applicant: Splunk Inc.
Inventor： Manish Sainani , Nghi Huu Nguyen , Zidong Yang
Abstract: Embodiments of the present invention are directed to facilitating enhancement of time series prediction. In accordance with aspects of the present disclosure, a set of time series data is determined to have at least one missing data value. Based on the missing data value(s), a predicted missing value is generated for each of the at least one missing data values. The predicted missing value for a missing data value is generated, for example, based on a weighted average of a time series data value preceding the missing data value and a time series data value following the missing data value. The set of time series data and the predicted missing values for each of the at least one missing data values can then be used to determine periodicity associated with the set of time series data.
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公开(公告)号：US20160103838A1
公开(公告)日：2016-04-14
申请号：US14859248
申请日：2015-09-18
Applicant: Splunk Inc.
Inventor： Manish Sainani , Adam Jamison Oliner , Jacob Barton Leverich , Leonid Alekseyev , Sonal Barton Maheshwari
IPC: G06F17/30 , G06F3/0488
CPC classification number: G06F3/0488 , H04L41/22 , H04L41/5012 , H04L41/5032 , H04L41/5045
Abstract: Techniques are disclosed for anomaly detection. A search query can be executed over a period of time to produce values for a key performance indicator (KPI), the search query defining the KPI and deriving a value indicative of the performance of a service at a point in time or during a period of time, the value derived from machine data pertaining to one or more entities that provide the service. A graphical user interface (GUI) enabling a user to indicate a sensitivity setting can be displayed. A user input indicating the sensitivity setting can be received via the GUI. Zero or more of the values as anomalies can be identified in consideration of the sensitivity setting indicated by the user input. A GUI including information related to the values identified as anomalies can be d
Abstract translation: 公开了用于异常检测的技术。 可以在一段时间内执行搜索查询以产生关键性能指标（KPI）的值，搜索查询定义KPI并且在一个时间点或在一段时间内导出指示服务的性能的值 时间，从提供服务的一个或多个实体的机器数据导出的值。 可以显示使用户能够指示灵敏度设置的图形用户界面（GUI）。 可以通过GUI接收指示灵敏度设置的用户输入。 可以考虑由用户输入指示的灵敏度设置来识别零个或多个作为异常的值。 包括与识别为异常的值相关的信息的GUI可以是d
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公开(公告)号：US20160103559A1
公开(公告)日：2016-04-14
申请号：US14859233
申请日：2015-09-18
Applicant: Splunk Inc.
Inventor： Sonal Maheshwari , Manish Sainani , Leonid Alekseyev , Alan Hardin , Jacob Barton Leverich , Adam Jamison Oliner , Brian Reyes , Alok Anant Bhide
IPC: G06F3/0481 , G06F17/30 , G06T11/20
CPC classification number: G06F3/0481 , G06F3/04812 , G06F17/30548 , G06F17/30554 , G06Q10/00 , G06T11/206 , H04L67/1095
Abstract: Techniques are disclosed for providing a graphical user interface (GUI) for displaying and configuring adaptive or static thresholds for Key Performance Indicators (KPIs). The GUI may include one or more presentation schedules that may display threshold information associated with time policies. Each presentation schedule may include multiple time slots and span a portion of one or more time cycles. Some of the time slots may be associated with a specific time policy and may have a unifying appearance that distinguishes the time slots from timeslots associated with other time policies. The presentation schedules may arrange the time slots in a time grid arrangement (e.g., calendar grid view) or a graph arrangement with depictions (e.g., points, lines) that may illustrate KPI values and threshold markers that may illustrate the threshold values.
Abstract translation: 公开了用于提供用于显示和配置关键性能指标（KPI）的自适应或静态阈值的图形用户界面（GUI）的技术。 GUI可以包括可以显示与时间策略相关联的阈值信息的一个或多个呈现计划。 每个呈现时间表可以包括多个时隙并跨越一个或多个时间周期的一部分。 一些时隙可以与特定时间策略相关联，并且可以具有将时隙与与其他时间策略相关联的时隙区分开的统一外观。 呈现时间表可以以时间网格布置（例如，日历网格视图）或具有可以示出可以示出阈值的KPI值和阈值标记的图示（例如，点，线）的图形排列来布置时隙。
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