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    GEOMETRIC AGING DATA REDUCTION FOR MACHINE LEARNING APPLICATIONS
    61.
    发明申请
    GEOMETRIC AGING DATA REDUCTION FOR MACHINE LEARNING APPLICATIONS 有权

    公开(公告)号：US20220413481A1

    公开(公告)日：2022-12-29

    申请号：US17361189

    申请日：2021-06-28

    Applicant: Oracle International Corporation

    Inventor： Dieter Gawlick ,  Matthew Torin Gerdes ,  Kirk Bradley ,  Anna Chystiakova ,  Zhen Hua Liu ,  Guang Chao Wang ,  Kenny C. Gross

    IPC: G05B23/02 ,  G06K9/62 ,  G06N20/00 ,  G06F11/34

    Abstract: Techniques for geometric aging data reduction for machine learning applications are disclosed. In some embodiments, an artificial-intelligence powered system receives a first time-series dataset that tracks at least one metric value over time. The system then generates a second time-series dataset that includes a reduced version of a first portion of the time-series dataset and a non-reduced version of a second portion of the time-series dataset. The second portion of the time-series dataset may include metric values that are more recent than the first portion of the time-series dataset. The system further trains a machine learning model using the second time-series dataset that includes the reduced version of the first portion of the time-series dataset and the non-reduced version of the second portion of the time-series dataset. The trained model may be applied to reduced and/or non-reduced data to detect multivariate anomalies and/or provide other analytic insights.

    Knowledge-intensive data processing system
    62.
    发明授权
    Knowledge-intensive data processing system 有权

    公开(公告)号：US11468098B2

    公开(公告)日：2022-10-11

    申请号：US16917468

    申请日：2020-06-30

    Applicant: Oracle International Corporation

    Inventor： Eric S. Chan ,  Dieter Gawlick ,  Adel Ghoneimy ,  Zhen Hua Liu

    IPC: G06F16/28 ,  G06F16/27 ,  G06F16/9535 ,  G06F11/30 ,  G06F11/34 ,  G06F16/21

    Abstract: Embodiments of the invention provide systems and methods for managing and processing large amounts of complex and high-velocity data by capturing and extracting high-value data from low value data using big data and related technologies. Illustrative database systems described herein may collect and process data while extracting or generating high-value data. The high-value data may be handled by databases providing functions such as multi-temporality, provenance, flashback, and registered queries. In some examples, computing models and system may be implemented to combine knowledge and process management aspects with the near real-time data processing frameworks in a data-driven situation aware computing system.

    Supporting piecewise update of JSON document efficiently
    65.
    发明授权
    Supporting piecewise update of JSON document efficiently 有权

    公开(公告)号：US11341317B2

    公开(公告)日：2022-05-24

    申请号：US16863268

    申请日：2020-04-30

    Applicant: Oracle International Corporation

    Inventor： Zhen Hua Liu ,  Beda Christoph Hammerschmidt ,  Douglas James Mcmahon ,  Joshua Jeffrey Spiegel

    IPC: G06F40/146 ,  G06F16/22 ,  G06F16/23

    Abstract: Herein are fine grained updates to pieces of JavaScript object notation (JSON) documents by database statements that can update, delete, and insert parts of JSON documents. In an embodiment, a computer receives a request that specifies a modification of a JSON document that is stored in a compressed format in persistent storage. The modification adds additional content to the JSON document, and/or replaces an old value in the JSON document with a new value that is not a same size as the old value. The modification is recorded in a change log. The change log is eventually applied to the compressed format of the JSON document in the persistent storage without entirely rewriting the compressed format of the JSON document in the persistent storage.

    MSET-BASED PROCESS FOR CERTIFYING PROVENANCE OF TIME-SERIES DATA IN A TIME-SERIES DATABASE
    70.
    发明申请
    MSET-BASED PROCESS FOR CERTIFYING PROVENANCE OF TIME-SERIES DATA IN A TIME-SERIES DATABASE 审中-公开

    公开(公告)号：US20190197145A1

    公开(公告)日：2019-06-27

    申请号：US15850027

    申请日：2017-12-21

    Applicant: Oracle International Corporation

    Inventor： Kenny C. Gross ,  Dieter Gawlick ,  Zhen Hua Liu ,  Mengying Li

    IPC: G06F17/30

    CPC classification number: G06F16/2365 ,  G06F16/2477

    Abstract: The disclosed embodiments relate to a system that certifies provenance of time-series data in a time-series database. During operation, the system retrieves time-series data from the time-series database, wherein the time-series data comprises a sequence of observations comprising sensor readings for each signal in a set of signals. The system also retrieves multivariate state estimation technique (MSET) estimates, which were computed for the time-series data, from the time-series database. Next, the system performs a reverse MSET computation to produce reconstituted time-series data from the MSET estimates. The system then compares the reconstituted time-series data with the time-series data. If the reconstituted time-series data matches the original time-series data, the system certifies provenance for the time-series data.

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