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    Unsupervised method for classifying seasonal patterns
    62.
    发明授权
    Unsupervised method for classifying seasonal patterns 有权

    公开(公告)号：US10885461B2

    公开(公告)日：2021-01-05

    申请号：US15057062

    申请日：2016-02-29

    Applicant: Oracle International Corporation

    Inventor： Dustin Garvey ,  Uri Shaft ,  Lik Wong

    IPC: G06N20/00

    Abstract: Techniques are described for classifying seasonal patterns in a time series. In an embodiment, a set of time series data is decomposed to generate a noise signal and a dense signal, where the noise signal includes a plurality of sparse features from the set of time series data and the dense signal includes a plurality of dense features from the set of time series data. A set of one or more sparse features from the noise signal is selected for retention. After selecting the sparse features, a modified set of time series data is generated by combining the set of one or more sparse features with a set of one or more dense features from the plurality of dense features. At least one seasonal pattern is identified from the modified set of time series data. A summary for the seasonal pattern may then be generated and stored.

    SYSTEM FOR DETECTING AND CHARACTERIZING SEASONS
    66.
    发明申请
    SYSTEM FOR DETECTING AND CHARACTERIZING SEASONS 审中-公开

    公开(公告)号：US20190228022A1

    公开(公告)日：2019-07-25

    申请号：US16370227

    申请日：2019-03-29

    Applicant: Oracle International Corporation

    Inventor： Dustin Garvey ,  Uri Shaft ,  Lik Wong ,  Amit Ganesh

    IPC: G06F16/28 ,  G06F21/55 ,  G06F16/2458 ,  G06F17/18 ,  G06Q10/04

    Abstract: Techniques are described for characterizing and summarizing seasonal patterns detected within a time series. According to an embodiment, a set of time series data is analyzed to identify a plurality of instances of a season, where each instance corresponds to a respective sub-period within the season. A first set of instances from the plurality of instances are associated with a particular class of seasonal pattern. After classifying the first set of instances, a second set of instances may remain unclassified or otherwise may not be associated with the particular class of seasonal pattern. Based on the first and second set of instances, a summary may be generated that identifies one or more stretches of time that are associated with the particular class of seasonal pattern. The one or more stretches of time may span at least one sub-period corresponding to at least one instance in the second set of instances.

    System for detecting and characterizing seasons
    67.
    发明授权
    System for detecting and characterizing seasons 有权

    公开(公告)号：US10282459B2

    公开(公告)日：2019-05-07

    申请号：US15057065

    申请日：2016-02-29

    Applicant: Oracle International Corporation

    Inventor： Dustin Garvey ,  Uri Shaft ,  Lik Wong ,  Amit Ganesh

    IPC: G06F17/30 ,  G06F17/18 ,  G06F21/55 ,  G06Q10/04 ,  G06N99/00 ,  G06Q10/06

    Abstract: Techniques are described for characterizing and summarizing seasonal patterns detected within a time series. A set of time series data is analyzed to identify a plurality of instances of a season, where each instance corresponds to a respective sub-period within the season. A first set of instances from the plurality of instances are associated with a particular class of seasonal pattern. After classifying the first set of instances, a second set of instances may remain unclassified or otherwise may not be associated with the particular class of seasonal pattern. Based on the first and second set of instances, a summary may be generated that identifies one or more stretches of time that are associated with the particular class of seasonal pattern. The one or more stretches of time may span at least one sub-period corresponding to at least one instance in the second set of instances.

    Correlation-Based Analytic For Time-Series Data
    68.
    发明申请
    Correlation-Based Analytic For Time-Series Data 审中-公开

    公开(公告)号：US20190114244A1

    公开(公告)日：2019-04-18

    申请号：US16213152

    申请日：2018-12-07

    Applicant: Oracle International Corporation

    Inventor： Sampanna Salunke ,  Dustin Garvey ,  Uri Shaft ,  Lik Wong

    IPC: G06F11/34 ,  G06F11/07

    Abstract: Techniques are described for modeling variations in correlation to facilitate analytic operations. In one or more embodiments, at least one computing device receives first metric data that tracks a first metric for a first target resource and second metric data that tracks a second metric for a second target resource. In response to receiving the first metric data and the second metric data, the at least one computing device generates a time-series of correlation values that tracks correlation between the first metric and the second metric over time. Based at least in part on the time-series of correlation data, an expected correlation is determined and compared to an observed correlation. If the observed correlation falls outside of a threshold range or otherwise does not satisfy the expected correlation, then an alert and/or other output may be generated.

    Method for creating period profile for time-series data with recurrent patterns
    70.
    发明授权
    Method for creating period profile for time-series data with recurrent patterns 有权

    公开(公告)号：US10127695B2

    公开(公告)日：2018-11-13

    申请号：US15445763

    申请日：2017-02-28

    Applicant: Oracle International Corporation

    Inventor： Dustin Garvey ,  Uri Shaft ,  Lik Wong ,  Maria Kaval

    IPC: G06T11/20 ,  G06Q10/10 ,  G06T11/00

    Abstract: Techniques are described for generating period profiles. According to an embodiment, a set of time series data is received, where the set of time series data includes data spanning a plurality of time windows having a seasonal period. Based at least in part on the set of time-series data, a first set of sub-periods of the seasonal period is associated with a particular class of seasonal pattern. A profile for a seasonal period that identifies which sub-periods of the seasonal period are associated with the particular class of seasonal pattern is generated and stored, in volatile or non-volatile storage. Based on the profile, a visualization is generated for at least one sub-period of the first set of sub-periods of the seasonal period that indicates that the at least one sub-period is part of the particular class of seasonal pattern.

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