公开(公告)号：US20180052898A1

公开(公告)日：2018-02-22

申请号：US15683554

申请日：2017-08-22

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： David Allan ,  Alexander Sasha Stojanovic ,  Hassan Heidari Namarvar ,  Ganesh Seetharaman

IPC: G06F17/30 ,  G06F17/27 ,  G06N5/02 ,  G06N99/00 ,  G06F3/0482 ,  G06F17/18

CPC classification number: G06F8/433 ,  G06F3/0428 ,  G06F3/0482 ,  G06F3/0649 ,  G06F8/10 ,  G06F8/34 ,  G06F8/4452 ,  G06F9/5061 ,  G06F16/144 ,  G06F16/211 ,  G06F16/2322 ,  G06F16/2358 ,  G06F16/254 ,  G06F16/435 ,  G06F17/18 ,  G06F17/2785 ,  G06N5/022 ,  G06N5/04 ,  G06N5/046 ,  G06N20/00 ,  G06Q10/0637

Abstract: In accordance with various embodiments, described herein is a system (Data Artificial Intelligence system, Data AI system), for use with a data integration or other computing environment, that leverages machine learning (ML, DataFlow Machine Learning, DFML), for use in managing a flow of data (dataflow, DF), and building complex dataflow software applications (dataflow applications, pipelines). In accordance with an embodiment, the system can include a software development component and graphical user interface, referred to herein in some embodiments as a pipeline editor, or Lambda Studio IDE, that provides a visual environment for use with the system, including providing real-time recommendations for performing semantic actions on data accessed from an input HUB, based on an understanding of the meaning or semantics associated with the data.

公开(公告)号：US20180052897A1

公开(公告)日：2018-02-22

申请号：US15683551

申请日：2017-08-22

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： Hassan Heidari Namarvar ,  Alexander Sasha Stojanovic ,  David Allan ,  Ganesh Seetharaman

IPC: G06F17/30 ,  G06N5/02 ,  G06N99/00 ,  G06F3/0482 ,  G06F17/18

CPC classification number: G06F8/433 ,  G06F3/0428 ,  G06F3/0482 ,  G06F3/0649 ,  G06F8/10 ,  G06F8/34 ,  G06F8/4452 ,  G06F9/5061 ,  G06F16/144 ,  G06F16/211 ,  G06F16/2322 ,  G06F16/2358 ,  G06F16/254 ,  G06F16/435 ,  G06F17/18 ,  G06F17/2785 ,  G06N5/022 ,  G06N5/04 ,  G06N5/046 ,  G06N20/00 ,  G06Q10/0637

Abstract: In accordance with various embodiments, described herein is a system (Data Artificial Intelligence system, Data AI system), for use with a data integration or other computing environment, that leverages machine learning (ML, DataFlow Machine Learning, DFML), for use in managing a flow of data (dataflow, DF), and building complex dataflow software applications (dataflow applications, pipelines). In accordance with an embodiment, the system can provide support for auto-mapping of complex data structures, datasets or entities, between one or more sources or targets of data, referred to herein in some embodiments as HUBs. The auto-mapping can be driven by a metadata, schema, and statistical profiling of a dataset; and used to map a source dataset or entity associated with an input HUB, to a target dataset or entity or vice versa, to produce an output data prepared in a format or organization (projection) for use with one or more output HUBs.

公开(公告)号：US20180052878A1

公开(公告)日：2018-02-22

申请号：US15683567

申请日：2017-08-22

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： Ganesh Seetharaman ,  Alexander Sasha Stojanovic ,  Hassan Heidari Namarvar ,  David Allan

IPC: G06F17/30 ,  G06F3/06 ,  G06N5/02 ,  G06N99/00 ,  G06F3/0482

CPC classification number: G06F8/433 ,  G06F3/0428 ,  G06F3/0482 ,  G06F3/0649 ,  G06F8/10 ,  G06F8/34 ,  G06F8/4452 ,  G06F9/5061 ,  G06F16/144 ,  G06F16/211 ,  G06F16/2322 ,  G06F16/2358 ,  G06F16/254 ,  G06F16/435 ,  G06F17/18 ,  G06F17/2785 ,  G06N5/022 ,  G06N5/04 ,  G06N5/046 ,  G06N20/00 ,  G06Q10/0637

Abstract: In accordance with various embodiments, described herein is a system (Data Artificial Intelligence system, Data AI system), for use with a data integration or other computing environment, that leverages machine learning (ML, DataFlow Machine Learning, DFML), for use in managing a flow of data (dataflow, DF), and building complex dataflow software applications (dataflow applications, pipelines). In accordance with an embodiment, the system can provide data governance functionality such as, for example, provenance (where a particular data came from), lineage (how the data was acquired/processed), security (who was responsible for the data), classification (what is the data about), impact (how impactful is the data to a business), retention (how long should the data live), and validity (whether the data should be excluded/included for analysis/processing), for each slice of data pertinent to a particular snapshot in time; which can then be used in making lifecycle decisions and dataflow recommendations.

公开(公告)号：US11537371B2

公开(公告)日：2022-12-27

申请号：US17010665

申请日：2020-09-02

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： Ganesh Seetharaman ,  Alexander Sasha Stojanovic ,  Hassan Heidari Namarvar ,  David Allan

IPC: G06F16/00 ,  G06F8/41 ,  G06N20/00 ,  G06F16/14 ,  G06F16/21 ,  G06F16/25 ,  G06F16/435 ,  G06F16/23 ,  G06N5/04 ,  G06Q10/06 ,  G06F40/30 ,  G06F3/0482 ,  G06F17/18 ,  G06N5/02 ,  G06F8/10 ,  G06F8/34 ,  G06F3/042 ,  G06F3/06 ,  G06F9/50

Abstract: In accordance with various embodiments, described herein is a system (Data Artificial Intelligence system, Data AI system), for use with a data integration or other computing environment, that leverages machine learning (ML, DataFlow Machine Learning, DFML), for use in managing a flow of data (dataflow, DF), and building complex dataflow software applications (dataflow applications, pipelines). In accordance with an embodiment, the system provides a programmatic interface, referred to herein in some embodiments as a foreign function interface, by which a user or third-party can define a service, functional and business types, semantic actions, and patterns or predefined complex data flows based on functional and business types, in a declarative manner, to extend the functionality of the system.

公开(公告)号：US11537370B2

公开(公告)日：2022-12-27

申请号：US16845738

申请日：2020-04-10

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： Alexander Sasha Stojanovic ,  Hassan Heidari Namarvar ,  David Allan ,  Ganesh Seetharaman

IPC: G06F8/41 ,  G06N20/00 ,  G06F16/14 ,  G06F16/21 ,  G06F16/25 ,  G06F16/435 ,  G06F16/23 ,  G06N5/04 ,  G06Q10/06 ,  G06F40/30 ,  G06F3/0482 ,  G06F17/18 ,  G06N5/02 ,  G06F8/10 ,  G06F8/34 ,  G06F3/042 ,  G06F3/06 ,  G06F9/50

Abstract: In accordance with various embodiments, described herein is a system (Data Artificial Intelligence system, Data AI system), for use with a data integration or other computing environment, that leverages machine learning (ML, DataFlow Machine Learning, DFML), for use in managing a flow of data (dataflow, DF), and building complex dataflow software applications (dataflow applications, pipelines). In accordance with an embodiment, the system can perform an ontology analysis of a schema definition, to determine the types of data, and datasets or entities, associated with that schema; and generate, or update, a model from a reference schema that includes an ontology defined based on relationships between datasets or entities, and their attributes. A reference HUB including one or more schemas can be used to analyze data flows, and further classify or make recommendations such as, for example, transformations enrichments, filtering, or cross-entity data fusion of an input data.

公开(公告)号：US11379506B2

公开(公告)日：2022-07-05

申请号：US16237405

申请日：2018-12-31

Applicant: Oracle International Corporation

Inventor： Alexander Sasha Stojanovic ,  Mark Kreider ,  Michael Malak ,  Glenn Allen Murray

IPC: G06F16/35 ,  G06F16/33 ,  G06F16/215 ,  G06F16/248 ,  G06F16/25 ,  G06F16/28 ,  G06F16/901 ,  G06Q30/02 ,  G06Q30/06

Abstract: The present disclosure relates to performing similarity metric analysis and data enrichment using knowledge sources. A data enrichment service can compare an input data set to reference data sets stored in a knowledge source to identify similarly related data. A similarity metric can be calculated corresponding to the semantic similarity of two or more datasets. The similarity metric can be used to identify datasets based on their metadata attributes and data values enabling easier indexing and high performance retrieval of data values. A input data set can labeled with a category based on the data set having the best match with the input data set. The similarity of an input data set with a data set provided by a knowledge source can be used to query a knowledge source to obtain additional information about the data set. The additional information can be used to provide recommendations to the user.

公开(公告)号：US10976907B2

公开(公告)日：2021-04-13

申请号：US14864520

申请日：2015-09-24

Applicant: Oracle International Corporation

Inventor： Alexander Sasha Stojanovic ,  Douglas C. Savolainen ,  Mark Kreider

IPC: G06F16/21 ,  G06F16/22 ,  G06F16/23 ,  G06F16/9038 ,  G06F3/0484 ,  G06F3/0488 ,  G06T11/20

Abstract: Techniques are disclosure for a data enrichment system that enables declarative external data source importation and exportation. A user can specify via a user interface input for identifying different data sources from which to obtain input data. The data enrichment system is configured to import and export various types of sources storing resources such as URL-based resources and HDFS-based resources for high-speed bi-directional metadata and data interchange. Connection metadata (e.g., credentials, access paths, etc.) can be managed by the data enrichment system in a declarative format for managing and visualizing the connection metadata.

公开(公告)号：US10210246B2

公开(公告)日：2019-02-19

申请号：US14864485

申请日：2015-09-24

Applicant: Oracle International Corporation

Inventor： Alexander Sasha Stojanovic ,  Mark Kreider ,  Michael Malak ,  Glenn Allen Murray

IPC: G06F17/30 ,  G06Q30/02

Abstract: The present disclosure relates to performing similarity metric analysis and data enrichment using knowledge sources. A data enrichment service can compare an input data set to reference data sets stored in a knowledge source to identify similarly related data. A similarity metric can be calculated corresponding to the semantic similarity of two or more datasets. The similarity metric can be used to identify datasets based on their metadata attributes and data values enabling easier indexing and high performance retrieval of data values. A input data set can labeled with a category based on the data set having the best match with the input data set. The similarity of an input data set with a data set provided by a knowledge source can be used to query a knowledge source to obtain additional information about the data set. The additional information can be used to provide recommendations to the user.

公开(公告)号：US20160092557A1

公开(公告)日：2016-03-31

申请号：US14864485

申请日：2015-09-24

Applicant: Oracle International Corporation

Inventor： Alexander Sasha Stojanovic ,  Mark Kreider ,  Michael Malak ,  Glenn Allen Murray

IPC: G06F17/30

CPC classification number: G06F17/30675 ,  G06F17/30303 ,  G06F17/30554 ,  G06F17/30563 ,  G06F17/30598 ,  G06F17/30705 ,  G06F17/30958 ,  G06Q30/02

Abstract: The present disclosure relates to performing similarity metric analysis and data enrichment using knowledge sources. A data enrichment service can compare an input data set to reference data sets stored in a knowledge source to identify similarly related data. A similarity metric can be calculated corresponding to the semantic similarity of two or more datasets. The similarity metric can be used to identify datasets based on their metadata attributes and data values enabling easier indexing and high performance retrieval of data values. A input data set can labeled with a category based on the data set having the best match with the input data set. The similarity of an input data set with a data set provided by a knowledge source can be used to query a knowledge source to obtain additional information about the data set. The additional information can be used to provide recommendations to the user.

Abstract translation: 本公开涉及使用知识源来执行相似性度量分析和数据丰富。 数据丰富服务可以将输入数据集与存储在知识源中的参考数据集进行比较，以识别类似的相关数据。 可以对应于两个或更多个数据集的语义相似度来计算相似性度量。 相似性度量可以用于基于其元数据属性和数据值来识别数据集，从而实现数据值的索引和高性能检索。 输入数据集可以基于与输入数据集具有最佳匹配的数据集来标记类别。 输入数据集与由知识源提供的数据集的相似性可用于查询知识源以获得关于数据集的附加信息。 附加信息可用于向用户提供建议。

公开(公告)号：US20220269491A1

公开(公告)日：2022-08-25

申请号：US17738774

申请日：2022-05-06

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： Ganesh Seetharaman ,  Alexander Sasha Stojanovic ,  Hassan Heidari Namarvar ,  David Allan

IPC: G06F8/41 ,  G06N20/00 ,  G06F16/14 ,  G06F16/21 ,  G06F16/25 ,  G06F16/435 ,  G06F16/23 ,  G06N5/04 ,  G06Q10/06 ,  G06F40/30 ,  G06F3/0482 ,  G06F17/18 ,  G06N5/02 ,  G06F8/10 ,  G06F8/34 ,  G06F3/042 ,  G06F3/06

Abstract: In accordance with various embodiments, described herein is a system (Data Artificial Intelligence system, Data AI system), for use with a data integration or other computing environment, that leverages machine learning (ML, DataFlow Machine Learning, DFML), for use in managing a flow of data (dataflow, DF), and building complex dataflow software applications (dataflow applications, pipelines). In accordance with an embodiment, the system can provide data governance functionality such as, for example, provenance (where a particular data came from), lineage (how the data was acquired/processed), security (who was responsible for the data), classification (what is the data about), impact (how impactful is the data to a business), retention (how long should the data live), and validity (whether the data should be excluded/included for analysis/processing), for each slice of data pertinent to a particular snapshot in time; which can then be used in making lifecycle decisions and dataflow recommendations.