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公开(公告)号：US20210168184A1
公开(公告)日：2021-06-03
申请号：US17174317
申请日：2021-02-11
Applicant: Netflix, Inc.
Inventor： Mohammad Hossein Taghavi , Prasanna Padmanabhan , Dong-Bang Tsai , Faisal Zakaria Siddiqi , Justin Derrick Basilico
Abstract: A system for utilizing models derived from offline historical data in online applications is provided. The system includes a processor and a memory storing machine-readable instructions for determining a set of contexts of the usage data, and for each of the contexts within the set of contexts, collecting service data from services supporting the media service and storing that service data in a database. The system performing an offline testing process by fetching service data for a defined context from the database, generating a first set of feature vectors based on the fetched service data, and providing the first set to a machine-learning module. The system performs an online testing process by fetching active service data from the services supporting the media streaming service, generating a second set of feature vectors based on the fetched active service data, and providing the second set to the machine-learning module.
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公开(公告)号：US11522938B2
公开(公告)日：2022-12-06
申请号：US17174317
申请日：2021-02-11
Applicant: Netflix, Inc.
Inventor： Mohammad Hossein Taghavi , Prasanna Padmanabhan , Dong-Bang Tsai , Faisal Zakaria Siddiqi , Justin Derrick Basilico
IPC: H04L65/75 , G06N5/04 , G06N20/00 , H04L65/70 , H04L67/50 , H04L67/306 , H04N21/24 , G06F16/335 , G06F16/9535 , H04L67/303 , H04N21/25 , H04N21/258
Abstract: A system for utilizing models derived from offline historical data in online applications is provided. The system includes a processor and a memory storing machine-readable instructions for determining a set of contexts of the usage data, and for each of the contexts within the set of contexts, collecting service data from services supporting the media service and storing that service data in a database. The system performing an offline testing process by fetching service data for a defined context from the database, generating a first set of feature vectors based on the fetched service data, and providing the first set to a machine-learning module. The system performs an online testing process by fetching active service data from the services supporting the media streaming service, generating a second set of feature vectors based on the fetched active service data, and providing the second set to the machine-learning module.
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公开(公告)号：US20190394252A1
公开(公告)日：2019-12-26
申请号：US16557558
申请日：2019-08-30
Applicant: Netflix, Inc.
Inventor： Mohammad Hossein Taghavi , Prasanna Padmanabhan , Dong-Bang Tsai , Faisal Zakaria Siddiqi , Justin Derrick Basilico
Abstract: A system for utilizing models derived from offline historical data in online applications is provided. The system includes a processor and a memory storing machine-readable instructions for determining a set of contexts of the usage data, and for each of the contexts within the set of contexts, collecting service data from services supporting the media service and storing that service data in a database. The system performing an offline testing process by fetching service data for a defined context from the database, generating a first set of feature vectors based on the fetched service data, and providing the first set to a machine-learning module. The system performs an online testing process by fetching active service data from the services supporting the media streaming service, generating a second set of feature vectors based on the fetched active service data, and providing the second set to the machine-learning module.
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公开(公告)号：US20240403713A1
公开(公告)日：2024-12-05
申请号：US18679215
申请日：2024-05-30
Applicant: Netflix, Inc.
Inventor： Ding Tong , Qifeng Qiao , Justin Derrick Basilico , Ting-Po Lee , James McInerney
IPC: G06N20/00
Abstract: A computer-implemented method includes identifying offline evaluation metrics that indicate, for a given feedback loop in a recommendation system, various feedback loop characteristics that are detrimental to the feedback loop. The method also includes generating a predictive machine learning (ML) model that correlates the identified offline evaluation metrics with indications of those feedback loop characteristics that are detrimental to the feedback loop. The method further includes instantiating the predictive ML model to predict, using the correlated offline evaluation metrics and the detrimental feedback loop characteristics, how the feedback loop will be negatively affected over time, and providing, to at least one entity, an indication of how the feedback loop will be negatively affected over time due to the detrimental feedback loop characteristics. Various other methods, systems, and computer-readable media are also disclosed.
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Patent Agency Ranking
公开(公告)号：US11782821B2
公开(公告)日：2023-10-10
申请号：US17853648
申请日：2022-06-29
Applicant: Netflix, Inc.
Inventor： David Gevorkyan , Mehmet Yilmaz , Ajinkya More , Justin Derrick Basilico , Prasanna Padmanabhan , Vivek Kaushal , Gaurav Agrawal , Richard Wellington
CPC classification number: G06F11/3664 , G06F11/3608 , G06F16/22
Abstract: The disclosed computer-implemented method may include accessing updated data structures that are to be included in a user interface functionality test, where the updated data structures contribute to a user interface. The method may also include accessing live or snapshotted data captured from services running in a production environment, initiating generation of a first user interface instance using the updated data structures and using the accessed live or snapshotted data, and initiating generation of a second user interface instance using a different version of the data structures and using the same accessed live or snapshotted data. The method further includes comparing the first user interface instance to the second user interface instance to identify differences and then determine which outcome-defining effects the updated data structures had on the user interface based on the identified differences between the user interfaces. Various other methods, systems, and computer-readable media are also disclosed.
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公开(公告)号：US20210141712A1
公开(公告)日：2021-05-13
申请号：US16746795
申请日：2020-01-17
Applicant: Netflix, Inc.
Inventor： David Gevorkyan , Mehmet Yilmaz , Ajinkya More , Justin Derrick Basilico , Prasanna Padmanabhan , Vivek Kaushal , Gaurav Agrawa , Richard Wellington
Abstract: The disclosed computer-implemented method may include accessing updated data structures that are to be included in a user interface functionality test, where the updated data structures contribute to a user interface. The method may also include accessing live or snapshotted data captured from services running in a production environment, initiating generation of a first user interface instance using the updated data structures and using the accessed live or snapshotted data, and initiating generation of a second user interface instance using a different version of the data structures and using the same accessed live or snapshotted data. The method further includes comparing the first user interface instance to the second user interface instance to identify differences and then determine which outcome-defining effects the updated data structures had on the user interface based on the identified differences between the user interfaces. Various other methods, systems, and computer-readable media are also disclosed.
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公开(公告)号：US11409637B2
公开(公告)日：2022-08-09
申请号：US16746795
申请日：2020-01-17
Applicant: Netflix, Inc.
Inventor： David Gevorkyan , Mehmet Yilmaz , Ajinkya More , Justin Derrick Basilico , Prasanna Padmanabhan , Vivek Kaushal , Gaurav Agrawal , Richard Wellington
Abstract: The disclosed computer-implemented method may include accessing updated data structures that are to be included in a user interface functionality test, where the updated data structures contribute to a user interface. The method may also include accessing live or snapshotted data captured from services running in a production environment, initiating generation of a first user interface instance using the updated data structures and using the accessed live or snapshotted data, and initiating generation of a second user interface instance using a different version of the data structures and using the same accessed live or snapshotted data. The method further includes comparing the first user interface instance to the second user interface instance to identify differences and then determine which outcome-defining effects the updated data structures had on the user interface based on the identified differences between the user interfaces. Various other methods, systems, and computer-readable media are also disclosed.
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公开(公告)号：US10958704B2
公开(公告)日：2021-03-23
申请号：US16557558
申请日：2019-08-30
Applicant: Netflix, Inc.
Inventor： Mohammad Hossein Taghavi , Prasanna Padmanabhan , Dong-Bang Tsai , Faisal Zakaria Siddiqi , Justin Derrick Basilico
IPC: H04L29/06 , G06N5/04 , G06F16/335 , H04L29/08 , G06N20/00 , H04N21/24 , G06F16/9535 , H04N21/25 , H04N21/258
Abstract: A system for utilizing models derived from offline historical data in online applications is provided. The system includes a processor and a memory storing machine-readable instructions for determining a set of contexts of the usage data, and for each of the contexts within the set of contexts, collecting service data from services supporting the media service and storing that service data in a database. The system performing an offline testing process by fetching service data for a defined context from the database, generating a first set of feature vectors based on the fetched service data, and providing the first set to a machine-learning module. The system performs an online testing process by fetching active service data from the services supporting the media streaming service, generating a second set of feature vectors based on the fetched active service data, and providing the second set to the machine-learning module.
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公开(公告)号：US10432689B2
公开(公告)日：2019-10-01
申请号：US15331106
申请日：2016-10-21
Applicant: NETFLIX, Inc
Inventor： Mohammad Hossein Taghavi , Prasanna Padmanabhan , Dong-Bang Tsai , Faisal Zakaria Siddiqi , Justin Derrick Basilico
IPC: H04L29/06 , H04L29/08 , G06N5/04 , G06N20/00 , H04N21/24 , G06F16/335 , G06F16/9535 , H04N21/25 , H04N21/258
Abstract: A system for utilizing models derived from offline historical data in online applications is provided. The system includes a processor and a memory storing machine-readable instructions for determining a set of contexts of the usage data, and for each of the contexts within the set of contexts, collecting service data from services supporting the media service and storing that service data in a database. The system performing an offline testing process by fetching service data for a defined context from the database, generating a first set of feature vectors based on the fetched service data, and providing the first set to a machine-learning module. The system performs an online testing process by fetching active service data from the services supporting the media streaming service, generating a second set of feature vectors based on the fetched active service data, and providing the second set to the machine-learning module.
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