ANOMALOUS DATA IDENTIFICATION FOR TABULAR DATA

    公开(公告)号:US20240320538A1

    公开(公告)日:2024-09-26

    申请号:US18123673

    申请日:2023-03-20

    Applicant: ADOBE INC.

    CPC classification number: G06N20/00

    Abstract: Systems and methods identify anomalous data in tabular data. A set of tabular data records is received. Each tabular data record includes data elements for a numbers of attributes, with each data element providing a value for a corresponding attribute. An anomaly score is generated for each data element of each tabular data record. Additionally, an evidence set is defined for each attribute and each tabular data record based on the anomaly scores for the data elements. An anomaly score is generated for each attribute and each tabular data record using the evidence sets. An output is provided that identifies one or more anomalous data subsets determined based on the anomaly scores for the attributes and tabular data records. Each anomalous data subset identifies a subset of attributes and a subset of tabular data records.

    SYSTEMS AND METHODS FOR CONFIGURING DATA STREAM FILTERING

    公开(公告)号:US20230281203A1

    公开(公告)日:2023-09-07

    申请号:US17685223

    申请日:2022-03-02

    Applicant: ADOBE INC.

    CPC classification number: G06F16/24568

    Abstract: Systems and methods for configuring data stream filtering are disclosed. In one embodiment, a method for data stream processing comprises receiving an incoming dataset stream at a data stream processing environment, wherein the dataset stream comprises a data stream; configuring with a streaming data filter configuration tool, one or more filter parameters for a data filter that receives the data stream; computing with the streaming data filter configuration tool, one or more filter statistics estimates based on the filter parameters, wherein the filter statistics estimates are computed from sample elements of a representative sample of the data stream retrieved from a representative sample data store; outputting to a workstation user interface the filter statistics estimates; and configuring the data filter to apply the filter parameters to the data stream in response to an instruction from the workstation user interface.

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