中科微点-全球专利检索

  1. Login
  2. Sign Up

Search Results

7 records (took 0.016 seconds)

    DRAG-AND-DROP ON A MOBILE DEVICE
    1.
    发明申请
    DRAG-AND-DROP ON A MOBILE DEVICE 审中-公开

    公开(公告)号：US20170153782A1

    公开(公告)日：2017-06-01

    申请号：US15432493

    申请日：2017-02-14

    Applicant: GOOGLE INC.

    Inventor： Matthew SHARIFI ,  David PETROU

    IPC: G06F3/0486 ,  G06F3/16 ,  G06F3/0488

    CPC classification number: G06F3/0486 ,  G06F3/04842 ,  G06F3/0488 ,  G06F3/04883 ,  G06F3/167 ,  G06F9/543 ,  G06F2203/04803

    Abstract: Implementations provide an improved drag-and-drop operation on a mobile device. For example, a method includes identifying a drag area in a user interface of a first mobile application in response to a drag command and receiving a drop location in a second mobile application that differs from the first mobile application. The method may also include determining that a drop location is a text input control and the drag area is not text-based, performing a search for a text description of the drag area, and pasting the text description into the text input control. The method may also include determining that a drop location is an image input control and that the drag area is text based, performing a search using the drag area for a responsive image, and pasting the responsive image into the image input control.

    MODELING PERSONAL ENTITIES
    3.
    发明申请
    MODELING PERSONAL ENTITIES 审中-公开
    建立个人实体

    公开(公告)号：US20170032257A1

    公开(公告)日：2017-02-02

    申请号：US14812877

    申请日：2015-07-29

    Applicant: GOOGLE INC.

    Inventor： Matthew SHARIFI ,  David PETROU ,  Pranav KHAITAN

    IPC: G06N5/04 ,  G06F3/0481 ,  G06N99/00 ,  G06F17/30

    Abstract: Systems and methods are provided for a personal entity modeling for computing devices. For example, a computing device comprises at least one processor and memory storing instructions that, when executed by the at least one processor, cause the mobile device to perform operations including identifying a personal entity in content generated for display on the mobile device, generating training examples for the personal entity from the content, and updating an embedding used to model the personal entity using the training examples. The embedding may be used to make predictions regarding the personal entity. For example, the operations may also include predicting an association between a first personal entity displayed on the computing device and a second entity based on the embedding, and providing a recommendation, to be displayed on the computing device, related to the second entity.

    Abstract translation: 为计算设备的个人实体建模提供了系统和方法。 例如，计算设备包括至少一个处理器和存储器，其存储指令，当所述至少一个处理器执行时，所述指令使得所述移动设备执行操作，所述操作包括在所生成的用于在所述移动设备上显示的内容中识别个人实体，生成训练 从个人实体的内容的示例，以及使用培训示例更新用于建模个人实体的嵌入。 嵌入可用于对个人实体进行预测。 例如，所述操作还可以包括基于所述嵌入来预测显示在所述计算设备上的第一个人实体与第二实体之间的关联，以及提供要显示在所述计算设备上的与所述第二实体相关的推荐。

    SIMULATED HYPERLINKS ON A MOBILE DEVICE
    5.
    发明申请
    SIMULATED HYPERLINKS ON A MOBILE DEVICE 审中-公开

    公开(公告)号：US20170139879A1

    公开(公告)日：2017-05-18

    申请号：US14945348

    申请日：2015-11-18

    Applicant: GOOGLE INC.

    Inventor： Matthew SHARIFI ,  David PETROU

    IPC: G06F17/22 ,  G06F3/0482 ,  G06F3/0484

    CPC classification number: G06F17/2235 ,  G06F3/0482 ,  G06F3/04842 ,  G06F9/453 ,  G06F9/4843

    Abstract: Systems and methods simulate a hyperlink in regular content displayed on a screen. An example method can include generating, responsive to detecting a simulated hyperlink indication, a centered selection from content displayed on a display of a computing device, providing the centered selection to a simulated hyperlink model that predicts an operation given the centered selection, and initiating the operation using an intent associated with a mobile application. The simulated hyperlink model may also provide, from the centered selection, an intelligent selection used the intent's parameter. Another method includes identifying documents having a hyperlink whitelisted websites, generating positive training examples for a simulated hyperlink model using the documents, each positive training example having a centered selection, a website, and a mobile application mapped to the website, and training the simulated hyperlink model, using the positive training examples, to predict an operation for the mobile application given the centered selection.

    SCREEN-ANALYSIS BASED DEVICE SECURITY
    7.
    发明申请
    SCREEN-ANALYSIS BASED DEVICE SECURITY 审中-公开
    基于屏幕分析的设备安全

    公开(公告)号：US20160366126A1

    公开(公告)日：2016-12-15

    申请号：US14739107

    申请日：2015-06-15

    Applicant: GOOGLE INC.

    Inventor： Matthew SHARIFI ,  Kai WANG ,  David PETROU

    IPC: H04L29/06 ,  G06N99/00 ,  H04W12/06

    CPC classification number: G06N99/005 ,  G06F21/316 ,  G06F21/36 ,  H04L63/083 ,  H04L63/102 ,  H04W4/02 ,  H04W4/80 ,  H04W12/06 ,  H04W12/10 ,  H04W12/12

    Abstract: Systems and methods are provided for a content-based security for computing devices. An example method includes identifying content rendered by a mobile application, the content being rendered during a session, generating feature vectors from the content and determining that the feature vectors do not match a classification model. The method also includes providing, in response to the determination that the feature vectors do not match the classification model, a challenge configured to authenticate a user of the mobile device. Another example method includes determining a computing device is located at a trusted location, capturing information from a session, the information coming from content rendered by a mobile application during the session, generating feature vectors for the session, and repeating this until a training criteria is met. The method also includes training a classification model using the feature vectors and authenticating a user of the device using the trained classification model.

    Abstract translation: 为计算设备的基于内容的安全提供了系统和方法。 示例性方法包括识别由移动应用呈现的内容，在会话期间呈现的内容，从内容生成特征向量并且确定特征向量与分类模型不匹配。 所述方法还包括响应于所述特征向量与所述分类模型不匹配的确定而提供配置用于认证所述移动设备的用户的挑战。 另一示例性方法包括确定计算设备位于可信位置，从会话中捕获信息，来自在会话期间由移动应用呈现的内容的信息，生成会话的特征向量，并重复此操作，直到训练标准为 见面 该方法还包括使用特征向量来训练分类模型，并使用经过训练的分类模型来验证该设备的用户。

Patent Agency Ranking