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    SEEDING AND GENERATING SUGGESTED CONTENT COLLECTIONS
    32.
    发明公开
    SEEDING AND GENERATING SUGGESTED CONTENT COLLECTIONS 审中-公开

    公开(公告)号：US20240273145A1

    公开(公告)日：2024-08-15

    申请号：US18605008

    申请日：2024-03-14

    Applicant: Dropbox, Inc.

    Inventor： Jongmin Baek ,  Jiarui Ding

    IPC: G06F16/906 ,  G06F3/0482 ,  G06F16/9035

    CPC classification number: G06F16/906 ,  G06F3/0482 ,  G06F16/9035

    Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and suggesting content collections for user accounts of a content management system using combinations of content-based features such as textual signals and visual signals. In some embodiments, the disclosed systems select a seed content item from among a plurality of content items associated with a user account within a content management system. From the seed content item, the disclosed systems can determine one or more germane topics and can cluster additional content items in relation to the germane topic(s). In addition, the disclosed systems can select one or more content items from a content cluster to provide as a suggested content collection.

    Seeding and generating suggested content collections
    34.
    发明授权
    Seeding and generating suggested content collections 有权

    公开(公告)号：US11947601B2

    公开(公告)日：2024-04-02

    申请号：US17815478

    申请日：2022-07-27

    Applicant: Dropbox, Inc.

    Inventor： Jongmin Baek ,  Jiarui Ding

    IPC: G06F16/906 ,  G06F3/0482 ,  G06F16/9035

    CPC classification number: G06F16/906 ,  G06F3/0482 ,  G06F16/9035

    Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and suggesting content collections for user accounts of a content management system using combinations of content-based features such as textual signals and visual signals. In some embodiments, the disclosed systems select a seed content item from among a plurality of content items associated with a user account within a content management system. From the seed content item, the disclosed systems can determine one or more germane topics and can cluster additional content items in relation to the germane topic(s). In addition, the disclosed systems can select one or more content items from a content cluster to provide as a suggested content collection.

    UTILIZING A NATURAL LANGUAGE MODEL TO DETERMINE A PREDICTED ACTIVITY EVENT BASED ON A SERIES OF SEQUENTIAL TOKENS
    37.
    发明公开
    UTILIZING A NATURAL LANGUAGE MODEL TO DETERMINE A PREDICTED ACTIVITY EVENT BASED ON A SERIES OF SEQUENTIAL TOKENS 审中-公开

    公开(公告)号：US20230161648A1

    公开(公告)日：2023-05-25

    申请号：US18156275

    申请日：2023-01-18

    Applicant: Dropbox, Inc.

    Inventor： Ranjitha Gurunath Kulkarni ,  Xingyu Xiang ,  Jongmin Baek ,  Ermo Wei

    IPC: G06F9/54 ,  G06F40/284 ,  G06N3/08 ,  G06N5/02

    CPC classification number: G06F9/542 ,  G06F40/284 ,  G06N3/08 ,  G06N5/02

    Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that can leverage a natural language model to determine a most probable candidate sequence of tokens and thereby generate a predicted user activity. In particular, the disclosed systems can tokenize activity event vectors to generate a series of sequential tokens that correspond to recent user activity of one or more user accounts. In addition, the disclosed systems can, for each candidate (e.g., hypothetical) user activity, augment the series of sequential tokens to include a corresponding token. Based on respective probability scores for each of the augmented series of sequential tokens, the disclosed systems can identify as the predicted user activity, a candidate user activity corresponding to one of the augmented series of sequential tokens associated with a highest probability score. Based on the predicted user activity, the disclosed systems can surface one or more suggestions to a client device.

    Utilizing machine-learning models to generate identifier embeddings and determine digital connections between digital content items
    39.
    发明授权
    Utilizing machine-learning models to generate identifier embeddings and determine digital connections between digital content items 有权

    公开(公告)号：US11568018B2

    公开(公告)日：2023-01-31

    申请号：US17131488

    申请日：2020-12-22

    Applicant: Dropbox, Inc.

    Inventor： Jongmin Baek ,  Jiarui Ding ,  Ermo Wei ,  Scott McCrae

    IPC: G06F16/958 ,  G06N20/00 ,  G06N3/04 ,  G06F40/284

    Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that utilize machine learning models to generate identifier embeddings from digital content identifiers and then leverage these identifier embeddings to determine digital connections between digital content items. In particular, the disclosed systems can utilize an embedding machine-learning model that comprises a character-level embedding machine-learning model and a word-level embedding machine-learning model. For example, the disclosed systems can combine a character embedding from the character-level embedding machine-learning model and a token embedding from the word-level embedding machine-learning model. The disclosed systems can determine digital connections between the plurality of digital content items by processing these identifier embeddings for a plurality of digital content items utilizing a content management model. Based on the digital connections, the disclosed systems can surface one or more digital content suggestions to a user interface of a client device.

    Version history management
    40.
    发明授权
    Version history management 有权

    公开(公告)号：US11526533B2

    公开(公告)日：2022-12-13

    申请号：US15396191

    申请日：2016-12-30

    Applicant: Dropbox, Inc.

    Inventor： Jongmin Baek ,  Daniel Wagner ,  Yuyang Guo ,  Kimberly Watkins

    IPC: G06F16/27 ,  G06F16/21 ,  G06F16/23

    Abstract: A first client device associated with a first account of a content management system can receive a first or latest version of a synchronized content item. The first client device can determine differences or the “diff” between the first version and a second or next-to-latest version of the content item and upload the first version and the diff to the content management system. Upon receiving the first version and the diff, the content management system can store the first version and the diff and download them to the second client device. The second client device can generate a notification when the download finishes and present the notification with an interface element for requesting presentation of the diff. When the second client device detects a selection of the interface element, the second client device can present the diff.

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