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    ENHANCING DOCUMENTS PORTRAYED IN DIGITAL IMAGES
    11.
    发明申请
    ENHANCING DOCUMENTS PORTRAYED IN DIGITAL IMAGES 审中-公开

    公开(公告)号：US20180024974A1

    公开(公告)日：2018-01-25

    申请号：US15658289

    申请日：2017-07-24

    Applicant: DROPBOX, INC.

    Inventor： Nils Peter Welinder ,  Peter N. Belhumeur ,  Ying Xiong ,  Jongmin Baek ,  Simon Kozlov ,  Thomas Berg ,  David J. Kriegman

    IPC: G06F17/24 ,  G06K9/00 ,  G06T11/00 ,  G06F17/22 ,  G06F17/21 ,  G06T7/194

    Abstract: The present disclosure is directed toward systems and methods that efficiently and effectively generate an enhanced document image of a displayed document in an image frame captured from a live image feed. For example, systems and methods described herein apply a document enhancement process to a displayed document in an image frame that result in an enhanced document image that is cropped, rectified, un-shadowed, and with dark text against a mostly white background. Additionally, systems and method described herein determine whether a stored digital content item includes a displayed document. In response to determining that a stored digital content item does include a displayed document, systems and methods described herein generate an enhanced document image of a displayed document included in the stored digital content item.

    CONTENT TYPE EMBEDDINGS
    12.
    发明申请
    CONTENT TYPE EMBEDDINGS 有权

    公开(公告)号：US20240419753A1

    公开(公告)日：2024-12-19

    申请号：US18813653

    申请日：2024-08-23

    Applicant: Dropbox, Inc.

    Inventor： Jongmin Baek ,  Jiarui Ding ,  Neeraj Kumar

    IPC: G06F16/957 ,  G06F16/178 ,  G06F16/2457 ,  G06F18/2413 ,  G06N3/047 ,  G06N3/08 ,  G06N7/01 ,  G06N20/10 ,  G06V10/764 ,  G06V10/82

    Abstract: Techniques for learning and using content type embeddings. The content type embeddings have the useful property that a distance in an embedding space between two content type embeddings corresponds to a semantic similarity between the two content types represented by the two content type embeddings. The closer the distance in the space, the more the two content types are semantically similar. The farther the distance in the space, the less the two content types are semantically similar. The learned content type embeddings can be used in a content suggestion system as machine learning features to improve content suggestions to end-users.

    SEEDING AND GENERATING SUGGESTED CONTENT COLLECTIONS
    13.
    发明公开
    SEEDING AND GENERATING SUGGESTED CONTENT COLLECTIONS 审中-公开

    公开(公告)号：US20240037154A1

    公开(公告)日：2024-02-01

    申请号：US17815478

    申请日：2022-07-27

    Applicant: Dropbox, Inc.

    Inventor： Jongmin Baek ,  Jiarui Ding

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

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

    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.

    Generating and providing collections of collaborative content items to teams of user accounts
    14.
    发明授权
    Generating and providing collections of collaborative content items to teams of user accounts 有权

    公开(公告)号：US11853968B2

    公开(公告)日：2023-12-26

    申请号：US17153686

    申请日：2021-01-20

    Applicant: Dropbox, Inc.

    Inventor： Jongmin Baek ,  Sarah Andrabi ,  Kristian Concepcion

    IPC: G06Q10/0633 ,  G06Q10/101

    CPC classification number: G06Q10/101 ,  G06Q10/0633

    Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and providing team-specific collections of collaborative content items. For example, the disclosed systems can determine relationships between teams of user accounts and various collaborative content items. Based on the determined relationships, the disclosed systems can identify which collaborative content items are germane to which teams and can provide the collaborative content items to user accounts accordingly. As part of determining relationships between collaborative content items and user accounts (or teams of user accounts), the disclosed systems can determine various information pertaining to the collaborative content items, including access patterns, sharing patterns, activity information, and geographic information.

    Utilizing a natural language model to determine a predicted activity event based on a series of sequential tokens
    15.
    发明授权
    Utilizing a natural language model to determine a predicted activity event based on a series of sequential tokens 有权

    公开(公告)号：US11853817B2

    公开(公告)日：2023-12-26

    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.

    CLASSIFYING AND ORGANIZING DIGITAL CONTENT ITEMS AUTOMATICALLY UTILIZING CONTENT ITEM CLASSIFICATION MODELS
    17.
    发明公开
    CLASSIFYING AND ORGANIZING DIGITAL CONTENT ITEMS AUTOMATICALLY UTILIZING CONTENT ITEM CLASSIFICATION MODELS 审中-公开

    公开(公告)号：US20230185768A1

    公开(公告)日：2023-06-15

    申请号：US17548516

    申请日：2021-12-11

    Applicant: Dropbox, Inc.

    Inventor： Tristan Inghelbrecht ,  Jongmin Baek ,  Ermo Wei ,  Morgan Zerby ,  Win Suen ,  Shubham Goel

    IPC: G06N20/00

    CPC classification number: G06N20/00

    Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that utilize machine-learning models to classify content items and automatically organize the content items within a file structure according to their content item classifications. For instance, a content item classification system generates one or more content item classification models to determine classifications for content items and/or folders. In some instances, the classification system detects when new content items are added to a smart folder, determines destination folders to which the content items belong based on classifying the content items, and automatically moves the content items accordingly. In various instances, the classification system generates and utilizes a classification model to organize content items into dynamically-generated folders. In example implementations, the classification system generates and utilizes a classification model to automatically organize existing content items into existing folders.

    GENERATING AND PROVIDING COLLECTIONS OF COLLABORATIVE CONTENT ITEMS TO TEAMS OF USER ACCOUNTS
    18.
    发明申请
    GENERATING AND PROVIDING COLLECTIONS OF COLLABORATIVE CONTENT ITEMS TO TEAMS OF USER ACCOUNTS 有权

    公开(公告)号：US20220230138A1

    公开(公告)日：2022-07-21

    申请号：US17153686

    申请日：2021-01-20

    Applicant: Dropbox, Inc.

    Inventor： Jongmin Baek ,  Sarah Andrabi ,  Kristian Concepcion

    IPC: G06Q10/10 ,  G06Q10/06

    Abstract: The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and providing team-specific collections of collaborative content items. For example, the disclosed systems can determine relationships between teams of user accounts and various collaborative content items. Based on the determined relationships, the disclosed systems can identify which collaborative content items are germane to which teams and can provide the collaborative content items to user accounts accordingly. As part of determining relationships between collaborative content items and user accounts (or teams of user accounts), the disclosed systems can determine various information pertaining to the collaborative content items, including access patterns, sharing patterns, activity information, and geographic information.

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