DATA CLASSIFICATION WORKFLOWS IMPLEMENTED WITH DYNAMICALLY MODIFIABLE DIRECTED GRAPHS

    公开(公告)号:US20180004835A1

    公开(公告)日:2018-01-04

    申请号:US15199403

    申请日:2016-06-30

    Applicant: Facebook, Inc.

    CPC classification number: G06N20/00 G06F16/20 G06N5/022

    Abstract: Various embodiments include a classification platform system. A user can define a classification experiment on the classification platform system. For example, the user can define an input data space by selecting at least one of data sources interfaced with the classification platform system and defining a directed graph (DG) connecting a plurality of transformation blocks to represent an experiment workflow. The DG can specify how one or more outputs of each of the transformation blocks are fed into one or more other transformation blocks. At least one of the transformation block can dynamically modify the DG. The classification platform system can schedule the experiment workflow to be executed on a distributed computation platform according to the input data space and the DG.

    Computation platform agnostic data classification workflows

    公开(公告)号:US10698954B2

    公开(公告)日:2020-06-30

    申请号:US15199351

    申请日:2016-06-30

    Applicant: Facebook, Inc.

    Abstract: Various embodiments include a classification platform system. A user can define a classification experiment on the classification platform system. For example, the user can define an input data space by selecting at least one of data sources interfaced with the classification platform system and defining a workflow configuration including a directed graph (DG) connecting a plurality of transformation blocks to represent an experiment workflow. The DG can specify how one or more outputs of each of the transformation blocks are fed into one or more other transformation blocks. The DG can be executed by various types of computation platforms. The classification platform system can schedule the experiment workflow to be executed on a distributed computation platform according to the input data space and the workflow configuration.

    GRAPHICALLY MANAGING DATA CLASSIFICATION WORKFLOWS IN A SOCIAL NETWORKING SYSTEM WITH DIRECTED GRAPHS

    公开(公告)号:US20190354554A1

    公开(公告)日:2019-11-21

    申请号:US16530587

    申请日:2019-08-02

    Applicant: Facebook, Inc.

    Abstract: In one embodiment, a method includes defining an input data space, defining a directed graph (DG) connecting a plurality of transformation blocks to represent an experiment workflow, wherein at least one of the plurality of transformation blocks includes logic to dynamically modify the DG during execution of the experiment workflow, formatting the DG and the input data space into a data structure such that the data structure is interpretable by a plurality of different computation platforms, scheduling a distributed computation platform selected from the plurality of different computation platforms to execute the experiment workflow according to the input data space and the DG, and imperatively programming computing nodes of the distributed computation platform to execute the experiment workflow based on the DG if at least one of the transformation blocks dynamically modifies the DG during the execution of the experiment workflow.

    Graphically managing data classification workflows in a social networking system with directed graphs

    公开(公告)号:US10459979B2

    公开(公告)日:2019-10-29

    申请号:US15199335

    申请日:2016-06-30

    Applicant: Facebook, Inc.

    Abstract: Various embodiments include a classification platform system. A user can define a classification experiment on the classification platform system. For example, the user can define an input data space by selecting at least one of data sources interfaced with the classification platform system and defining a workflow configuration including a directed graph (DG) connecting a plurality of transformation blocks to represent an experiment workflow. The DG can specify how one or more outputs of each of the transformation blocks are fed into one or more other transformation blocks. The DG can be defined graphically. The classification platform system can schedule the experiment workflow to be executed on a distributed computation platform according to the input data space and the workflow configuration.

    COMPUTATION PLATFORM AGNOSTIC DATA CLASSIFICATION WORKFLOWS

    公开(公告)号:US20180004859A1

    公开(公告)日:2018-01-04

    申请号:US15199351

    申请日:2016-06-30

    Applicant: Facebook, Inc.

    Abstract: Various embodiments include a classification platform system. A user can define a classification experiment on the classification platform system. For example, the user can define an input data space by selecting at least one of data sources interfaced with the classification platform system and defining a workflow configuration including a directed graph (DG) connecting a plurality of transformation blocks to represent an experiment workflow. The DG can specify how one or more outputs of each of the transformation blocks are fed into one or more other transformation blocks. The DG can be executed by various types of computation platforms. The classification platform system can schedule the experiment workflow to be executed on a distributed computation platform according to the input data space and the workflow configuration.

    COMPUTATION PLATFORM AGNOSTIC DATA CLASSIFICATION WORKFLOWS

    公开(公告)号:US20200334293A1

    公开(公告)日:2020-10-22

    申请号:US16916040

    申请日:2020-06-29

    Applicant: FACEBOOK, INC.

    Abstract: Various embodiments include a classification platform system. A user can define a classification experiment on the classification platform system. For example, the user can define an input data space by selecting at least one of data sources interfaced with the classification platform system and defining a workflow configuration including a directed graph (DG) connecting a plurality of transformation blocks to represent an experiment workflow. The DG can specify how one or more outputs of each of the transformation blocks are fed into one or more other transformation blocks. The DG can be executed by various types of computation platforms. The classification platform system can schedule the experiment workflow to be executed on a distributed computation platform according to the input data space and the workflow configuration.

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