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公开(公告)号：US11561933B2
公开(公告)日：2023-01-24
申请号：US17220260
申请日：2021-04-01
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Paul Ireifej , Mohammad Omar Khalid Mirza , Prince Paulraj , Heather Wighton , Christopher Kim , Stephen Grandinetti , Mger Babayan
Abstract: Aspects of the subject disclosure may include, for example, receiving input data via a transformation UI, generating transformation configuration data, causing the transformation UI to present transformation object data per the transformation configuration data, where the transformation object data identifies data objects each including an input and output field name and a data type, detecting, from the transformation UI, an instruction defining a mapping for the input data, including a modification to the output field name of a data object such that the input field name of the data object is mapped to the modified output field name, based on the detecting the instruction, modifying the first transformation configuration data per the mapping to derive second transformation configuration data, performing a transformation of the input data based on the second transformation configuration data, and causing the transformation UI to present a transformation output. Other embodiments are disclosed.
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公开(公告)号：US20230143392A1
公开(公告)日：2023-05-11
申请号：US18149787
申请日：2023-01-04
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Paul Ireifej , Mohammad Omar Khalid Mirza , Prince Paulraj , Heather Wighton , Christopher Kim , Stephen Grandinetti , Mger Babayan
CPC classification number: G06F16/168 , G06F16/256 , G06F16/258
Abstract: Aspects of the subject disclosure may include, for example, receiving input data via a transformation UI, generating transformation configuration data, causing the transformation UI to present transformation object data per the transformation configuration data, where the transformation object data identifies data objects each including an input and output field name and a data type, detecting, from the transformation UI, an instruction defining a mapping for the input data, including a modification to the output field name of a data object such that the input field name of the data object is mapped to the modified output field name, based on the detecting the instruction, modifying the first transformation configuration data per the mapping to derive second transformation configuration data, performing a transformation of the input data based on the second transformation configuration data, and causing the transformation UI to present a transformation output. Other embodiments are disclosed.
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Patent Agency Ranking
公开(公告)号：US20240311340A1
公开(公告)日：2024-09-19
申请号：US18676675
申请日：2024-05-29
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Paul Ireifej , Mohammad Omar Khalid Mirza , Prince Paulraj , Heather Wighton , Christopher Kim , Stephen Grandinetti , Mger Babayan
CPC classification number: G06F16/168 , G06F16/256 , G06F16/258
Abstract: Aspects of the subject disclosure may include, for example, receiving input data via a transformation UI, generating transformation configuration data, causing the transformation UI to present transformation object data per the transformation configuration data, where the transformation object data identifies data objects each including an input and output field name and a data type, detecting, from the transformation UI, an instruction defining a mapping for the input data, including a modification to the output field name of a data object such that the input field name of the data object is mapped to the modified output field name, based on the detecting the instruction, modifying the first transformation configuration data per the mapping to derive second transformation configuration data, performing a transformation of the input data based on the second transformation configuration data, and causing the transformation UI to present a transformation output. Other embodiments are disclosed.
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公开(公告)号：US12032520B2
公开(公告)日：2024-07-09
申请号：US18149787
申请日：2023-01-04
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Paul Ireifej , Mohammad Omar Khalid Mirza , Prince Paulraj , Heather Wighton , Christopher Kim , Stephen Grandinetti , Mger Babayan
CPC classification number: G06F16/168 , G06F16/256 , G06F16/258
Abstract: Aspects of the subject disclosure may include, for example, receiving input data via a transformation UI, generating transformation configuration data, causing the transformation UI to present transformation object data per the transformation configuration data, where the transformation object data identifies data objects each including an input and output field name and a data type, detecting, from the transformation UI, an instruction defining a mapping for the input data, including a modification to the output field name of a data object such that the input field name of the data object is mapped to the modified output field name, based on the detecting the instruction, modifying the first transformation configuration data per the mapping to derive second transformation configuration data, performing a transformation of the input data based on the second transformation configuration data, and causing the transformation UI to present a transformation output. Other embodiments are disclosed.
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公开(公告)号：US20230214711A1
公开(公告)日：2023-07-06
申请号：US17646708
申请日：2021-12-31
Applicant: AT&T INTELLECTUAL PROPERTY I, L.P.
Inventor： Prince Paulraj , Christopher Kim , Eric Zavesky , Prathiba Sugumaran , James Pratt , Cuong Vo
Abstract: A method performed by a processing system including at least one processor includes detecting that new data has been added to a repository of reusable machine learning models and machine learning model features, applying data protection to the new data, testing the new data for bias, merging at least a portion of the new data with stored data from the repository to build a new machine learning model in which the data protection is preserved, and publishing the new machine learning model in the repository.
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公开(公告)号：US20220318194A1
公开(公告)日：2022-10-06
申请号：US17220260
申请日：2021-04-01
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Paul Ireifej , Mohammad Omar Khalid Mirza , Prince Paulraj , Heather Wighton , Christopher Kim , Stephen Grandinetti , Mger Babayan
Abstract: Aspects of the subject disclosure may include, for example, receiving input data via a transformation UI, generating transformation configuration data, causing the transformation UI to present transformation object data per the transformation configuration data, where the transformation object data identifies data objects each including an input and output field name and a data type, detecting, from the transformation UI, an instruction defining a mapping for the input data, including a modification to the output field name of a data object such that the input field name of the data object is mapped to the modified output field name, based on the detecting the instruction, modifying the first transformation configuration data per the mapping to derive second transformation configuration data, performing a transformation of the input data based on the second transformation configuration data, and causing the transformation UI to present a transformation output. Other embodiments are disclosed.
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公开(公告)号：US20210117977A1
公开(公告)日：2021-04-22
申请号：US16655390
申请日：2019-10-17
Applicant: AT&T Intellectual Property I, L.P.
Inventor： Christopher Kim , Mohammad Omar Khalid Mirza , Eric Noble
Abstract: A processing system including at least one processor may obtain at least one of a first machine learning model or a second machine learning model, deploy the at least one of the first machine learning model or the second machine learning model to a plurality of trained machine learning models for operating in parallel with respect to a same prediction task, obtain at least one data set, apply the at least one data set to the plurality of trained machine learning models, obtain the first result of the first machine learning model and a second result of the second machine learning model in accordance with the applying, store the first result of the first machine learning model and the second result of the second machine learning model, and provide an output in accordance with at least one of the first result or the second result.
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