公开(公告)号：US20200334244A1

公开(公告)日：2020-10-22

申请号：US16389304

申请日：2019-04-19

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： Beda Christoph HAMMERSCHMIDT ,  Zhen Hua LIU ,  Vikas ARORA ,  CHANDRASEKHARAN IYER ,  Beethoven CHENG ,  Ying HU ,  Douglas James McMahon

IPC: G06F16/242 ,  G06F16/25 ,  G06F9/448 ,  G06F8/41 ,  G06F8/76

Abstract: Described is a system, method, and computer program product to perform bi-directional mapping of hierarchical data (e.g. JSON, XML) to database object types (e.g., user defined database object types).

公开(公告)号：US20210295210A1

公开(公告)日：2021-09-23

申请号：US16826478

申请日：2020-03-23

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： Edward R. WETHERBEE ,  Kenneth P. BACLAWSKI ,  Guang C. WANG ,  Kenny C. GROSS ,  Anna CHYSTIAKOVA ,  Dieter GAWLICK ,  Zhen Hua LIU ,  Richard Paul SONDEREGGER

IPC: G06N20/00 ,  G06F17/16 ,  G06F17/18 ,  G06F30/27

Abstract: In one embodiment, a method for auditing the results of a machine learning model includes: retrieving a set of state estimates for original time series data values from a database under audit; reversing the state estimation computation for each of the state estimates to produce reconstituted time series data values for each of the state estimates; retrieving the original time series data values from the database under audit; comparing the original time series data values pairwise with the reconstituted time series data values to determine whether the original time series and reconstituted time series match; and generating a signal that the database under audit (i) has not been modified where the original time series and reconstituted time series match, and (ii) has been modified where the original time series and reconstituted time series do not match.

公开(公告)号：US20190102450A1

公开(公告)日：2019-04-04

申请号：US15807336

申请日：2017-11-08

Applicant: Oracle International Corporation

Inventor： Zhen Hua LIU ,  Geeta Arora ,  Hui Joe Chang

IPC: G06F17/30

Abstract: An approach for improving LOB query performance via automatic inference of locator-less LOB by value semantics in a relational database system is provided. A relational database management system (RDBMS) is implemented to perform operations on LOBs based on the semantics of a statement. During statement compilation, the RDBMS identifies inline LOB column(s) that are not required to be returned to a client. During execution, the identified column(s) are accessed via a shared buffer cache and fed to an operator for evaluation. For inline LOB column(s) that must be returned to the client, during execution, the inline LOB data is copied from the shared buffer cache to a temporary buffer area. Data in the temporary buffer area is fed to an operator for evaluation and is used to create a LOB locator for the inline LOB column(s) that must be returned to the client.

公开(公告)号：US20240265308A1

公开(公告)日：2024-08-08

申请号：US18615599

申请日：2024-03-25

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： Edward R. WETHERBEE ,  Kenneth P. BACLAWSKI ,  Guang C. WANG ,  Kenny C. GROSS ,  Anna MORAV ,  Dieter GAWLICK ,  Zhen Hua LIU ,  Richard Paul SONDEREGGER

IPC: G06N20/00 ,  G05B23/02 ,  G06F17/16 ,  G06F17/18 ,  G06F30/27 ,  G06F111/10 ,  G06N3/08 ,  G06N20/10

CPC classification number: G06N20/00 ,  G05B23/024 ,  G06F17/16 ,  G06F17/18 ,  G06F30/27 ,  G06F2111/10 ,  G06N3/08 ,  G06N20/10

Abstract: Systems, methods, and other embodiments associated with auditing the results of a machine learning model are described. In one embodiment, a method accesses original time series data and machine learning estimates of the original time series data. The method generates reconstituted time series data from the machine learning estimates by reversing operations of a machine learning model trained for generating the machine learning estimates from the original time series data. The method detects tampering (or corruption) in the original time series data based on a difference between the original time series data and reconstituted time series data. And, the method generates an electronic verification report that indicates whether the tampering (or corruption) is detected in the original time series data.

公开(公告)号：US20230376837A1

公开(公告)日：2023-11-23

申请号：US17751083

申请日：2022-05-23

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： Matthew T. GERDES ,  Kenneth P. BACLAWSKI ,  Dieter GAWLICK ,  Kenny C. GROSS ,  Guang Chao WANG ,  Anna CHYSTIAKOVA ,  Richard P. SONDEREGGER ,  Zhen Hua LIU

IPC: G06N20/00

CPC classification number: G06N20/00

Abstract: Systems, methods, and other embodiments associated with associated with dependency checking for machine learning (ML) models are described. In one embodiment, a method includes applying a repeating probe signal to an input signal input into a machine learning model. An estimate signal output from the machine learning model is monitored, and the repeating probe signal is checked for in the estimate signal. Based on the results of the checking for the repeating probe signal, an evaluation of dependency in the machine learning model is presented.

公开(公告)号：US20210081421A1

公开(公告)日：2021-03-18

申请号：US16570356

申请日：2019-09-13

Applicant: Oracle International Corporation

Inventor： Zhen Hua LIU ,  Geeta ARORA ,  Sriram KRISHNAMURTHY ,  Sneha CHANDRABABU ,  Sunitha SUBRAMANYAM

IPC: G06F16/2455 ,  G06F16/28 ,  G06F16/22

Abstract: Described are improved systems, computer program products, and methods for an improved approach to access small to medium size objects (MOBs) stored in LOB data type columns of a RDBMS. The approach includes receiving a SQL statement comprising a retrieval of a large object (LOB). The approach also includes determining whether to return a value of the LOB or a reference to a storage location storing the value of the LOB based on: a data dictionary property of the LOB to return the value of the LOB, a function included in the SQL statement to return the value of the LOB, or a flag derived from a SQL operator tree propagation to return the value of the LOB.