Patents by Inventor SHANG CAI
SHANG CAI has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11669382Abstract: 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.Type: GrantFiled: December 20, 2019Date of Patent: June 6, 2023Assignee: Splunk Inc.Inventors: Jacob Barton Leverich, Shang Cai, Hongyang Zhang, Mihai Ganea, Alex Cruise
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Patent number: 11632383Abstract: 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.Type: GrantFiled: October 21, 2020Date of Patent: April 18, 2023Assignee: Splunk Inc.Inventors: Adam Jamison Oliner, Jonathan La, Colleen Kinross, Hongyang Zhang, Jacob Leverich, Shang Cai, Mihai Ganea, Alex Cruise, Toufic Boubez, Manish Sainani
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Patent number: 10992560Abstract: 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.Type: GrantFiled: December 20, 2018Date of Patent: April 27, 2021Assignee: SPLUNK INC.Inventors: Jacob Barton Leverich, Shang Cai, Hongyang Zhang, Mihai Ganea, Alex Cruise
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Publication number: 20210037037Abstract: 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.Type: ApplicationFiled: October 21, 2020Publication date: February 4, 2021Inventors: ADAM JAMISON OLINER, JONATHAN LA, COLLEEN KINROSS, HONGYANG ZHANG, JACOB LEVERICH, SHANG CAI, MIHAI GANEA, ALEX CRUISE, TOUFIC BOUBEZ, MANISH SAINANI
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Patent number: 10855712Abstract: 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.Type: GrantFiled: June 19, 2019Date of Patent: December 1, 2020Assignee: SPLUNK Inc.Inventors: Adam Jamison Oliner, Jonathan La, Colleen Kinross, Hongyang Zhang, Jacob Leverich, Shang Cai, Mihai Ganea, Alex Cruise, Toufic Boubez, Manish Sainani
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Publication number: 20200125433Abstract: 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.Type: ApplicationFiled: December 20, 2019Publication date: April 23, 2020Inventors: Jacob Barton Leverich, Shang Cai, Hongyang Zhang, Mihai Ganea, Alex Cruise
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Patent number: 10558516Abstract: 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.Type: GrantFiled: October 31, 2018Date of Patent: February 11, 2020Assignee: SPLUNK INC.Inventors: Jacob Barton Leverich, Shang Cai, Hongyang Zhang, Mihai Ganea, Alex Cruise
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Publication number: 20190306184Abstract: 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.Type: ApplicationFiled: June 19, 2019Publication date: October 3, 2019Inventors: ADAM JAMISON OLINER, JONATHAN LA, COLLEEN KINROSS, HONGYANG ZHANG, JACOB LEVERICH, SHANG CAI, MIHAI GANEA, ALEX CRUISE, TOUFIC BOUBEZ, MANISH SAINANI
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Patent number: 10375098Abstract: 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.Type: GrantFiled: January 31, 2017Date of Patent: August 6, 2019Inventors: Adam Jamison Oliner, Jonathan La, Colleen Kinross, Hongyang Zhang, Jacob Leverich, Shang Cai, Mihai Ganea, Alex Cruise, Toufic Boubez, Manish Sainani
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Publication number: 20190123988Abstract: 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.Type: ApplicationFiled: December 20, 2018Publication date: April 25, 2019Inventors: Jacob Barton Leverich, Shang Cai, Hongyang Zhang, Mihai Ganea, Alex Cruise
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Publication number: 20190065298Abstract: 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.Type: ApplicationFiled: October 31, 2018Publication date: February 28, 2019Inventors: Jacob Barton Leverich, Shang Cai, Hongyang Zhang, Mihai Ganea, Alex Cruise
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Patent number: 10200262Abstract: 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.Type: GrantFiled: July 8, 2016Date of Patent: February 5, 2019Assignee: Splunk Inc.Inventors: Jacob Barton Leverich, Shang Cai, Hongyang Zhang, Mihai Ganea, Alex Cruise
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Patent number: 10146609Abstract: 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.Type: GrantFiled: July 8, 2016Date of Patent: December 4, 2018Assignee: SPLUNK INC.Inventors: Jacob Barton Leverich, Shang Cai, Hongyang Zhang, Mihai Ganea, Alex Cruise
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Publication number: 20180219889Abstract: 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.Type: ApplicationFiled: January 31, 2017Publication date: August 2, 2018Inventors: ADAM JAMISON OLINER, JONATHAN LA, COLLEEN KINROSS, HONGYANG ZHANG, JACOB LEVERICH, SHANG CAI, MIHAI GANEA, ALEX CRUISE, TOUFIC BOUBEZ, MANISH SAINANI