HYPERCUBE ENCODING OF TEXT FOR NATURAL LANGUAGE PROCESSING

    公开(公告)号:US20220327278A1

    公开(公告)日:2022-10-13

    申请号:US17225041

    申请日:2021-04-07

    Abstract: An example method is provided for encoding text for language processing. The method may be executed by a processing system, and the method includes receiving text comprising a plurality of alphanumeric characters or symbols and converting the text into a numerical vector comprising a plurality of numerical values, by mapping each alphanumeric character or symbol of the text to a vertex coordinate of one of a plurality of vertices of a hypercube, wherein a number of the plurality of vertices is equal to or greater than a number of the plurality of alphanumeric characters or symbols, wherein the numerical vector consumes less space in memory than the text. An amount of time consumed by language processing of the numerical vector may be less than an amount of time consumed by language processing of the text.

    Converting text to a numerical vector by mapping to a hypercube

    公开(公告)号:US11675965B2

    公开(公告)日:2023-06-13

    申请号:US17225041

    申请日:2021-04-07

    CPC classification number: G06F40/126 G06F40/123

    Abstract: An example method is provided for encoding text for language processing. The method may be executed by a processing system, and the method includes receiving text comprising a plurality of alphanumeric characters or symbols and converting the text into a numerical vector comprising a plurality of numerical values, by mapping each alphanumeric character or symbol of the text to a vertex coordinate of one of a plurality of vertices of a hypercube, wherein a number of the plurality of vertices is equal to or greater than a number of the plurality of alphanumeric characters or symbols, wherein the numerical vector consumes less space in memory than the text. An amount of time consumed by language processing of the numerical vector may be less than an amount of time consumed by language processing of the text.

    Location Sharing Service
    8.
    发明申请
    Location Sharing Service 有权
    位置共享服务

    公开(公告)号:US20160234265A1

    公开(公告)日:2016-08-11

    申请号:US14614717

    申请日:2015-02-05

    Inventor: Sachin Lohe

    CPC classification number: H04L65/403 H04L12/1822 H04L51/20

    Abstract: Concepts and technologies are disclosed herein for providing a location sharing service. A server computer executing a location sharing service can identify a presenter for a location sharing session and a participant in the location sharing session. The server computer can receive location information from the presenter. The location information can identify a location accessed at a computing device associated with the presenter during a conference. The server computer can provide the location information to a user device associated with the participant during the conference. The server computer also can provide a log including the location information to the user device during or after the conference.

    Abstract translation: 这里公开了用于提供位置共享服务的概念和技术。 执行位置共享服务的服务器计算机可以识别位置共享会话的演示者和位置共享会话中的参与者。 服务器计算机可以从演示者接收位置信息。 位置信息可以在会议期间识别在与演示者相关联的计算设备处访问的位置。 服务器计算机可以在会议期间向与参与者相关联的用户设备提供位置信息。 在会议期间或之后,服务器计算机还可以向用户设备提供包括位置信息的日志。

    TIME SERIES ANOMALY DETECTION AND VISUALIZATION

    公开(公告)号:US20230067842A1

    公开(公告)日:2023-03-02

    申请号:US17463950

    申请日:2021-09-01

    Abstract: A processing system including at least one processor may generate a plurality of subsequences of a time series data set, convert the plurality of subsequences to a plurality of frequency domain point sets, compute pairwise distances of the plurality of frequency domain point sets, project the plurality of frequency domain point sets into a lower dimensional space in accordance with the pairwise distances, where the projecting maps each of plurality of frequency domain point sets to a node of a plurality of nodes in the lower dimensional space, and generate a notification of at least one isolated node of the plurality of nodes, where the at least one isolated node represents at least one anomaly in the time series data set.

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