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公开(公告)号:US20220180186A1
公开(公告)日:2022-06-09
申请号:US17192515
申请日:2021-03-04
Applicant: NETFLIX, INC.
Inventor: Justin Derrick BASILICO , Jiangwei PAN
IPC: G06N3/08
Abstract: Various embodiments set forth systems and techniques for training a personalized prediction model. The techniques include generating, based on interaction data associated with one or more users and a first weight associated with the interaction data, a first set of training data; generating, based on the personalized prediction model, a predicted enjoyment signal associated with playback of a digital content item; generating, based on the first set of training data and the predicted enjoyment signal, a second set of training data; and updating one or more parameters of a personalized ranking model based on the second set of training data.
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公开(公告)号:US20220334951A1
公开(公告)日:2022-10-20
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 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:US20170237792A1
公开(公告)日:2017-08-17
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
CPC classification number: H04L65/602 , G06F16/335 , G06F16/9535 , G06N5/04 , G06N20/00 , H04L65/607 , H04L67/22 , H04L67/303 , H04L67/306 , H04N21/2407 , H04N21/252 , H04N21/25891
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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