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    Methods and systems for input suggestion
    1.
    发明授权
    Methods and systems for input suggestion 有权

    公开(公告)号：US11803290B2

    公开(公告)日：2023-10-31

    申请号：US17156972

    申请日：2021-01-25

    Applicant: Google LLC

    Inventor： Tim Wantland ,  Julian Odell ,  Seungyeon Kim ,  Iulia Turc ,  Daniel Ramage ,  Wei Huang ,  Kaikai Wang

    IPC: G06F17/00 ,  G06F3/0482 ,  G06F3/0484

    CPC classification number: G06F3/0482 ,  G06F3/0484

    Abstract: The present disclosure is directed to input suggestion. In particular, the methods and systems of the present disclosure can: receive, from a first application executed by one or more computing devices, data indicating information that has been presented by and/or input into the first application; generate, based at least in part on the received data, one or more suggested candidate inputs for a second application executed by the computing device(s); provide, in association with the second application, an interface comprising one or more options to select at least one suggested candidate input of the suggested candidate input(s); and responsive to receiving data indicating a selection of a particular suggested candidate input of the suggested candidate input(s) via the interface, communicate, to the second application, data indicating the particular suggested candidate input.

    SYSTEMS AND METHODS FOR PRIVATE LOCAL SPONSORED CONTENT
    3.
    发明申请
    SYSTEMS AND METHODS FOR PRIVATE LOCAL SPONSORED CONTENT 有权

    公开(公告)号：US20210357986A1

    公开(公告)日：2021-11-18

    申请号：US17388708

    申请日：2021-07-29

    Applicant: Google LLC

    Inventor： Keith Bonawitz ,  Daniel Ramage ,  David Petrou

    IPC: G06Q30/02 ,  H04L9/00 ,  H04L29/06 ,  G06N5/02

    Abstract: Systems and methods are shown for providing private local sponsored content selection and improving intelligence models through distribution among mobile devices. This allows greater data gathering capabilities through the use of the sensors of the mobile devices as well as data stored on data storage components of the mobile devices to create predicted models while offering better opportunities to preserve privacy. Locally stored profiles comprising machine intelligence models may also be used to determine the relevance of the data gathered and in improving an aggregated model for identifying the relevance of data and the selection of sponsored content items. Distributed optimization is used in conjunction with privacy techniques to create the improved machine intelligence models. Publishers may also benefit from the improved privacy by protecting the statistics of type or volume of sponsored content items shown with publisher content.

    Localized learning from a global model
    4.
    发明授权
    Localized learning from a global model 有权

    公开(公告)号：US10824958B2

    公开(公告)日：2020-11-03

    申请号：US14468710

    申请日：2014-08-26

    Applicant: Google LLC

    Inventor： Daniel Ramage ,  Jeremy Gillmor Kahn

    IPC: G06N20/00 ,  H04L29/06

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for obtaining a global model for a particular activity, the global model derived based on input data representing multiple observations associated with the particular activity performed by a collection of users; determining, using the global model, expected data representing an expected observation associated with the particular activity performed by a particular user; receiving, by a computing device operated by the particular user, particular data representing an actual observation associated with the particular activity performed by the particular user; determining, by the computing device and using (i) the expected data and (ii) the particular data, residual data of the particular user; and deriving a local model of the particular user based on the residual data.

    SYSTEMS AND METHODS FOR PRIVATE LOCAL SPONSORED CONTENT
    7.
    发明公开
    SYSTEMS AND METHODS FOR PRIVATE LOCAL SPONSORED CONTENT 审中-公开

    公开(公告)号：US20230222551A1

    公开(公告)日：2023-07-13

    申请号：US18124174

    申请日：2023-03-21

    Applicant: GOOGLE LLC

    Inventor： Keith Bonawitz ,  Daniel Ramage ,  David Petrou

    IPC: H04L9/40 ,  H04L9/00

    CPC classification number: G06Q30/0269 ,  H04L9/008 ,  G06N5/025 ,  G06Q30/0251 ,  H04L63/0428 ,  G06Q30/0261

    Abstract: Systems and methods are shown for providing private local sponsored content selection and improving intelligence models through distribution among mobile devices. This allows greater data gathering capabilities through the use of the sensors of the mobile devices as well as data stored on data storage components of the mobile devices to create predicted models while offering better opportunities to preserve privacy. Locally stored profiles comprising machine intelligence models may also be used to determine the relevance of the data gathered and in improving an aggregated model for identifying the relevance of data and the selection of sponsored content items. Distributed optimization is used in conjunction with privacy techniques to create the improved machine intelligence models. Publishers may also benefit from the improved privacy by protecting the statistics of type or volume of sponsored content items shown with publisher content.

    Systems and methods for private local sponsored content
    9.
    发明授权
    Systems and methods for private local sponsored content 有权

    公开(公告)号：US11610231B2

    公开(公告)日：2023-03-21

    申请号：US17388708

    申请日：2021-07-29

    Applicant: Google LLC

    Inventor： Keith Bonawitz ,  Daniel Ramage ,  David Petrou

    IPC: G06Q30/02 ,  H04L9/00 ,  H04L9/40 ,  G06N5/02 ,  G06Q30/0251 ,  G06N5/025

    Abstract: Systems and methods are shown for providing private local sponsored content selection and improving intelligence models through distribution among mobile devices. This allows greater data gathering capabilities through the use of the sensors of the mobile devices as well as data stored on data storage components of the mobile devices to create predicted models while offering better opportunities to preserve privacy. Locally stored profiles comprising machine intelligence models may also be used to determine the relevance of the data gathered and in improving an aggregated model for identifying the relevance of data and the selection of sponsored content items. Distributed optimization is used in conjunction with privacy techniques to create the improved machine intelligence models. Publishers may also benefit from the improved privacy by protecting the statistics of type or volume of sponsored content items shown with publisher content.

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