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    CLUSTERING EVENTS WHILE EXCLUDING EXTRACTED VALUES
    2.
    发明申请
    CLUSTERING EVENTS WHILE EXCLUDING EXTRACTED VALUES 有权

    公开(公告)号：US20210149912A1

    公开(公告)日：2021-05-20

    申请号：US17158880

    申请日：2021-01-26

    Applicant: SPLUNK INC.

    Inventor： Jesse Brandau Miller ,  Katherine Kyle Feeney ,  Yuan Xie ,  Steve Zhang ,  Adam Jamison Oliner ,  Jindrich Dinga ,  Jacob Leverich

    IPC: G06F16/26

    Abstract: Systems and methods include causing presentation of a first cluster in association with an event of the first cluster, the first cluster from a first set of clusters of events. Each event includes a time stamp and event data. Based on the presentation of the first cluster, an extraction rule corresponding to the event of the first cluster is received from a user. Similarities in the event data between the events are determined based on the received extraction rule. The events are grouped into a second set of clusters based on the determined similarities. Presentation is caused of a second cluster in association with an event of the second cluster, where the second cluster is from the second set of clusters.

    Tool for machine-learning data analysis
    3.
    发明授权
    Tool for machine-learning data analysis 有权

    公开(公告)号：US10956834B2

    公开(公告)日：2021-03-23

    申请号：US16707845

    申请日：2019-12-09

    Applicant: Splunk Inc.

    Inventor： Manish Sainani ,  Sergey Slepian ,  Iman Makaremi ,  Adam Jamison Oliner ,  Jacob Leverich ,  Di Lu

    IPC: G06N20/00 ,  H04L12/24 ,  G06N5/02

    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.

    AUTOMATICALLY GENERATING FIELD EXTRACTION RECOMMENDATIONS
    4.
    发明申请
    AUTOMATICALLY GENERATING FIELD EXTRACTION RECOMMENDATIONS 审中-公开

    公开(公告)号：US20180089561A1

    公开(公告)日：2018-03-29

    申请号：US15420754

    申请日：2017-01-31

    Applicant: SPLUNK INC.

    Inventor： Adam Jamison Oliner ,  Nghi Huu Nguyen ,  Jacob Leverich ,  Zidong Yang

    IPC: G06N3/08 ,  G06F17/30

    Abstract: Systems and methods include obtaining a set of events, each event in the set of events comprising a time-stamped portion of raw machine data, the raw machine data produced by one or more components within an information technology or security environment and reflects activity within the information technology or security environment. Thereafter, a first neural network is used to automatically identify variable text to extract as a field from the set of events. An indication of the variable text is provided as a field extraction recommendation, for example, to a user device for presentation to a user.

    Clustering events while excluding extracted values
    5.
    发明授权
    Clustering events while excluding extracted values 有权

    公开(公告)号：US11657065B2

    公开(公告)日：2023-05-23

    申请号：US17158880

    申请日：2021-01-26

    Applicant: SPLUNK INC.

    Inventor： Jesse Brandau Miller ,  Katherine Kyle Feeney ,  Yuan Xie ,  Steve Zhang ,  Adam Jamison Oliner ,  Jindrich Dinga ,  Jacob Leverich

    IPC: G06F16/26

    CPC classification number: G06F16/26

    Abstract: Systems and methods include causing presentation of a first cluster in association with an event of the first cluster, the first cluster from a first set of clusters of events. Each event includes a time stamp and event data. Based on the presentation of the first cluster, an extraction rule corresponding to the event of the first cluster is received from a user. Similarities in the event data between the events are determined based on the received extraction rule. The events are grouped into a second set of clusters based on the determined similarities. Presentation is caused of a second cluster in association with an event of the second cluster, where the second cluster is from the second set of clusters.

    Automatically generating field extraction recommendations
    7.
    发明授权
    Automatically generating field extraction recommendations 有权

    公开(公告)号：US10685279B2

    公开(公告)日：2020-06-16

    申请号：US15420754

    申请日：2017-01-31

    Applicant: SPLUNK INC.

    Inventor： Adam Jamison Oliner ,  Nghi Huu Nguyen ,  Jacob Leverich ,  Zidong Yang

    IPC: G06F17/00 ,  G06N3/04 ,  G06F16/26 ,  G06F16/25

    Abstract: Systems and methods include obtaining a set of events, each event in the set of events comprising a time-stamped portion of raw machine data, the raw machine data produced by one or more components within an information technology or security environment and reflects activity within the information technology or security environment. Thereafter, a first neural network is used to automatically identify variable text to extract as a field from the set of events. An indication of the variable text is provided as a field extraction recommendation, for example, to a user device for presentation to a user.

    Methods and systems for determining probabilities of occurrence for events and determining anomalous events
    8.
    发明授权
    Methods and systems for determining probabilities of occurrence for events and determining anomalous events 有权

    公开(公告)号：US10572811B2

    公开(公告)日：2020-02-25

    申请号：US14609135

    申请日：2015-01-29

    Applicant: SPLUNK INC.

    Inventor： Nghi Nguyen ,  Jacob Leverich ,  Adam Oliner

    IPC: G06N7/00

    Abstract: Methods and systems for determining event probabilities and anomalous events are provided. In one implementation, a method includes: receiving source data, where the source data is configured as a plurality of events with associated timestamps; searching the source data, where the searching provides a search result including N events from the plurality of events, where N is an integer greater than one, where each event of the N events includes a plurality of field values, where at least one event of the N events can include one or more categorical field values and one or more numerical field values; and for an event of the N events, determining a probability of occurrence for each field value of the plurality of field values; and using probabilities determined for the plurality of field values, determining a probability of occurrence for the event.

    CLUSTERING EVENTS BASED ON EXTRACTION RULES
    9.
    发明申请
    CLUSTERING EVENTS BASED ON EXTRACTION RULES 审中-公开

    公开(公告)号：US20180089303A1

    公开(公告)日：2018-03-29

    申请号：US15276693

    申请日：2016-09-26

    Applicant: SPLUNK INC.

    Inventor： Jesse Brandau Miller ,  Katherine Kyle Feeney ,  Yuan Xie ,  Steve Zhang ,  Adam Jamison Oliner ,  Jindrich Dinga ,  Jacob Leverich

    IPC: G06F17/30

    CPC classification number: G06F16/26

    Abstract: Systems and methods include causing presentation of a first cluster in association with an event of the first cluster, the first cluster from a first set of clusters of events. Each event includes a time stamp and event data. Based on the presentation of the first cluster, an extraction rule corresponding to the event of the first cluster is received from a user. Similarities in the event data between the events are determined based on the received extraction rule. The events are grouped into a second set of clusters based on the determined similarities. Presentation is caused of a second cluster in association with an event of the second cluster, where the second cluster is from the second set of clusters.

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