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公开(公告)号：US09760240B2
公开(公告)日：2017-09-12
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: G06F15/16 , G06F3/0481 , G06T11/20 , G06F17/30 , H04L29/08
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.
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公开(公告)号：US11669382B2
公开(公告)日：2023-06-06
申请号：US16722673
申请日：2019-12-20
Applicant: SPLUNK INC.
Inventor： Jacob Barton Leverich , Shang Cai , Hongyang Zhang , Mihai Ganea , Alex Cruise
IPC: G06F11/07
CPC classification number: G06F11/079 , G06F11/0709 , G06F11/0793
Abstract: A continuous anomaly detection service receives data stream and performs continuous anomaly detection on the incoming data streams. This continuous anomaly detection is performed based on anomaly detection definitions, which define a signal used for anomaly detection and an anomaly detection configuration. These anomaly detection definitions can be modified, such that continuous anomaly detection continues to be performed for the data stream and the signal, based on the new anomaly detection definition.
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公开(公告)号：US10726030B2
公开(公告)日：2020-07-28
申请号：US14815954
申请日：2015-07-31
Applicant: Splunk Inc.
Inventor： Cory Eugene Burke , Jacob Barton Leverich , Jeffrey Thomas Lloyd , Adam Jamison Oliner , Marc Vincent Robichaud , Jesse Miller
IPC: G06F16/248 , G06F11/30 , G06F11/34 , G06F16/242 , G06F16/245
Abstract: A facility for defining an event subtype using examples is described. The facility displays events identified among machine-generated data. The facility receives user input selecting a first subset of the events as examples of an event subtype. In response to receiving the user input, the facility displays a second subset of the events predicted to belong to the event subtype on the basis of the examples of the event subtype.
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公开(公告)号：US20190147363A1
公开(公告)日：2019-05-16
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
IPC: G06N20/00
CPC classification number: G06N20/00
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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公开(公告)号：US20190123988A1
公开(公告)日：2019-04-25
申请号：US16227248
申请日：2018-12-20
Applicant: SPLUNK INC.
Inventor： Jacob Barton Leverich , Shang Cai , Hongyang Zhang , Mihai Ganea , Alex Cruise
Abstract: An anomaly detection system includes a plurality of signals. Each of the signals is associated with an anomaly detection procedure that will be used to identify anomalies within the signal. Anomaly detection is performed by applying the anomaly detection procedure to a sequential set of data points of a signal. The signals are updated based on incoming data streams. The data streams are analyzed, and the sequential set of data points for each signal is updated based on data points extracted from the data streams.
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Patent Agency Ranking
公开(公告)号：US20170329462A1
公开(公告)日：2017-11-16
申请号：US15662916
申请日：2017-07-28
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 , H04L29/08
CPC classification number: G06F3/0481 , G06F3/04812 , G06F16/2474 , G06F16/248 , G06Q10/06393 , G06Q10/109 , 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.
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公开(公告)号：US11875032B1
公开(公告)日：2024-01-16
申请号：US17732131
申请日：2022-04-28
Applicant: Splunk Inc.
Inventor： Manish Sainani , Adam Jamison Oliner , Jacob Barton Leverich , Leonid Alekseyev , Sonal Maheshwari
IPC: G06F15/16 , G06F3/0488 , G06F16/24 , G06F16/2458
CPC classification number: G06F3/0488 , G06F16/24 , G06F16/2462 , G06F16/2477
Abstract: Techniques are disclosed for anomaly detection based on a predicted value. 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.
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公开(公告)号：US10992560B2
公开(公告)日：2021-04-27
申请号：US16227248
申请日：2018-12-20
Applicant: SPLUNK INC.
Inventor： Jacob Barton Leverich , Shang Cai , Hongyang Zhang , Mihai Ganea , Alex Cruise
Abstract: An anomaly detection system includes a plurality of signals. Each of the signals is associated with an anomaly detection procedure that will be used to identify anomalies within the signal. Anomaly detection is performed by applying the anomaly detection procedure to a sequential set of data points of a signal. The signals are updated based on incoming data streams. The data streams are analyzed, and the sequential set of data points for each signal is updated based on data points extracted from the data streams.
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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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公开(公告)号：US10146609B1
公开(公告)日：2018-12-04
申请号：US15206126
申请日：2016-07-08
Applicant: Splunk, Inc.
Inventor： Jacob Barton Leverich , Shang Cai , Hongyang Zhang , Mihai Ganea , Alex Cruise
Abstract: A continuous anomaly detection service receives data stream and performs continuous anomaly detection on the incoming data streams. This continuous anomaly detection is performed based on anomaly detection definitions, which define a signal used for anomaly detection and an anomaly detection configuration. These anomaly detection definitions can be modified, such that continuous anomaly detection continues to be performed for the data stream and the signal, based on the new anomaly detection definition.
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