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公开(公告)号：US11636397B1
公开(公告)日：2023-04-25
申请号：US17582679
申请日：2022-01-24
Applicant: Splunk Inc.
Inventor： Manish Sainani , Nghi Huu Nguyen , Zidong Yang
IPC: G06N20/00 , G06F16/242 , G06F16/22 , G06F16/2458 , G06F16/248 , G06F16/26
Abstract: Embodiments of the present invention are directed to facilitating concurrent forecasting associating with multiple time series data sets. In accordance with aspects of the present disclosure, a request to perform a predictive analysis in association with multiple time series data sets is received. Thereafter, the request is parsed to identify each of the time series data sets to use in predictive analysis. For each time series data set, an object is initiated to perform the predictive analysis for the corresponding time series data set. Generally, the predictive analysis predicts expected outcomes based on the corresponding time series data set. Each object is concurrently executed to generate expected outcomes associated with the corresponding time series data set, and the expected outcomes associated with each of the corresponding time series data sets are provided for display.
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公开(公告)号：US10855712B2
公开(公告)日：2020-12-01
申请号：US16446300
申请日：2019-06-19
Applicant: SPLUNK INC.
Inventor： Adam Jamison Oliner , Jonathan La , Colleen Kinross , Hongyang Zhang , Jacob Leverich , Shang Cai , Mihai Ganea , Alex Cruise , Toufic Boubez , Manish Sainani
Abstract: In some implementations, sequences of time series values determined from machine data are obtained. Each sequence corresponds to a respective time series. A plurality of predictive models is generated for a first time series from the sequences of time series values. Each predictive model is to generate predicted values associated with the first time series using values of a second time series. For each of the plurality of predictive models, an error is determined between the corresponding predicted values and values associated with the first time series. A predictive model is selected for anomaly detection based on the determined error of the predictive model. Transmission is caused of an indication of an anomaly detected using the selected predictive model.
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公开(公告)号：US20190236210A1
公开(公告)日：2019-08-01
申请号：US15884090
申请日：2018-01-30
Applicant: SPLUNK INC.
Inventor： Iman Makaremi , Gyanendra Rana , Iryna Vogler-Ivashchanka , Adam Oliner , Harsh Keswani , Manish Sainani , Alexander Kim
Abstract: Operational machine components of an information technology (IT) or other microprocessor- or microcontroller-permeated environment generate disparate forms of machine data. Network connections are established between these components and processors of an automatic data intake and query system (DIQS). The DIQS conducts network transactions on a periodic and/or continuous basis with the machine components to receive the disparate data and ingest certain of the data as measurement entries of a DIQS metrics datastore that is searchable for DIQS query processing. The DIQS may receive search queries to process against the received and ingested data via an exposed network interface. In one example embodiment, a query building component conducts a user interface using a network attached client device. The query building component may elicit search criteria via the user interface using a natural language interface, construct a proper query therefrom, and present new information based on results returned from the DIQS.
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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：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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Patent Agency Ranking
公开(公告)号：US10726079B2
公开(公告)日：2020-07-28
申请号：US15884090
申请日：2018-01-30
Applicant: SPLUNK INC.
Inventor： Iman Makaremi , Gyanendra Rana , Iryna Vogler-Ivashchanka , Adam Oliner , Harsh Keswani , Manish Sainani , Alexander Kim
IPC: G06F15/173 , G06F16/951 , H04L12/24 , H04L29/08 , H04L29/06 , G06F16/2458 , G06F40/30
Abstract: Operational machine components of an information technology (IT) or other microprocessor- or microcontroller-permeated environment generate disparate forms of machine data. Network connections are established between these components and processors of an automatic data intake and query system (DIQS). The DIQS conducts network transactions on a periodic and/or continuous basis with the machine components to receive the disparate data and ingest certain of the data as measurement entries of a DIQS metrics datastore that is searchable for DIQS query processing. The DIQS may receive search queries to process against the received and ingested data via an exposed network interface. In one example embodiment, a query building component conducts a user interface using a network attached client device. The query building component may elicit search criteria via the user interface using a natural language interface, construct a proper query therefrom, and present new information based on results returned from the DIQS.
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公开(公告)号：US10375098B2
公开(公告)日：2019-08-06
申请号：US15420737
申请日：2017-01-31
Applicant: SPLUNK INC.
Inventor： Adam Jamison Oliner , Jonathan La , Colleen Kinross , Hongyang Zhang , Jacob Leverich , Shang Cai , Mihai Ganea , Alex Cruise , Toufic Boubez , Manish Sainani
Abstract: In some implementations, sequences of time series values determined from machine data are obtained. Each sequence corresponds to a respective time series. A plurality of predictive models is generated for a first time series from the sequences of time series values. Each predictive model is to generate predicted values associated with the first time series using values of a second time series. For each of the plurality of predictive models, an error is determined between the corresponding predicted values and values associated with the first time series. A predictive model is selected for anomaly detection based on the determined error of the predictive model. Transmission is caused of an indication of an anomaly detected using the selected predictive model.
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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：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：US20170220938A1
公开(公告)日：2017-08-03
申请号：US15143335
申请日：2016-04-29
Applicant: Splunk Inc.
Inventor： Manish Sainani , Nghi Huu Nguyen , Zidong Yang
Abstract: Embodiments of the present invention are directed to facilitating concurrent forecasting associating with multiple time series data sets. In accordance with aspects of the present disclosure, a request to perform a predictive analysis in association with multiple time series data sets is received. Thereafter, the request is parsed to identify each of the time series data sets to use in predictive analysis. For each time series data set, an object is initiated to perform the predictive analysis for the corresponding time series data set. Generally, the predictive analysis predicts expected outcomes based on the corresponding time series data set. Each object is concurrently executed to generate expected outcomes associated with the corresponding time series data set, and the expected outcomes associated with each of the corresponding time series data sets are provided for display.
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