公开(公告)号：US20190306184A1

公开(公告)日：2019-10-03

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

IPC: H04L29/06 ,  G06N3/04 ,  G06N3/08

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.

公开(公告)号：US20200167681A1

公开(公告)日：2020-05-28

申请号：US16776302

申请日：2020-01-29

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.

公开(公告)号：US20180219889A1

公开(公告)日：2018-08-02

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

IPC: H04L29/06 ,  G06N3/04 ,  G06N3/08

CPC classification number: H04L63/1425 ,  G06N3/08 ,  G06N5/003

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.

公开(公告)号：US20210037037A1

公开(公告)日：2021-02-04

申请号：US17075928

申请日：2020-10-21

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

IPC: H04L29/06 ,  G06N3/08 ,  G06N5/00 ,  G06N3/04

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.

公开(公告)号：US20160224899A1

公开(公告)日：2016-08-04

申请号：US14609135

申请日：2015-01-29

Applicant: SPLUNK INC.

Inventor： NGHI NGUYEN ,  JACOB LEVERICH ,  ADAM OLINER

IPC: G06N7/00 ,  G06N5/02

CPC classification number: G06N7/005

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.

Abstract translation: 提供了确定事件概率和异常事件的方法和系统。 在一个实现中，一种方法包括：接收源数据，其中源数据被配置为具有相关联的时间戳的多个事件; 搜索源数据，其中搜索提供包括来自多个事件的N个事件的搜索结果，其中N是大于1的整数，其中N个事件的每个事件包括多个字段值，其中至少一个事件 N个事件可以包括一个或多个分类字段值和一个或多个数字字段值; 并且对于N个事件的事件，确定多个字段值的每个字段值的出现概率; 以及使用为所述多个场值确定的概率，确定所述事件的发生概率。