AUTO-MONITORING AND ADJUSTMENT OF DYNAMIC DATA VISUALIZATIONS
    1.
    发明申请
    AUTO-MONITORING AND ADJUSTMENT OF DYNAMIC DATA VISUALIZATIONS 审中-公开
    自动监测和调整动态数据可视化

    公开(公告)号:US20170046404A1

    公开(公告)日:2017-02-16

    申请号:US14822776

    申请日:2015-08-10

    CPC classification number: G06F17/30554 G06F17/30867

    Abstract: Examples of auto-monitoring and adjusting dynamic data visualizations are provided herein. A data visualization based on initial data can be generated. A series of data updates can be received. The data visualization can be updated based on the series of data updates. Various performance metrics can be monitored, and data updates and/or the updated data visualization can be adjusted accordingly. Performance metrics can include at least one of: a data visualization rendering time; a data transfer time; or a data update generation time. Upon determining that one or more performance metrics exceed a threshold: a time between data updates of the series of data updates can be increased; sampled data can be requested for subsequent data updates; and/or a time-dimension extent of the updated data visualization can be reduced.

    Abstract translation: 本文提供了自动监控和调整动态数据可视化的示例。 可以生成基于初始数据的数据可视化。 可以接收一系列数据更新。 可以基于一系列数据更新来更新数据可视化。 可以监视各种性能指标,并可以相应地调整数据更新和/或更新的数据可视化。 性能指标可以包括以下至少一项:数据可视化呈现时间; 数据传输时间; 或数据更新生成时间。 在确定一个或多个性能指标超过阈值时:可以增加一系列数据更新的数据更新之间的时间; 可以请求采样数据进行后续数据更新; 和/或更新的数据可视化的时间维度范围可以减少。

    Natural language query system
    2.
    发明授权

    公开(公告)号:US11194850B2

    公开(公告)日:2021-12-07

    申请号:US16221114

    申请日:2018-12-14

    Abstract: A system includes reception of an input string of words, determination, for each subset of consecutive one or more words in the input string, of one or more phrase types based on the subset, on a dictionary describing a plurality of entities, each of the plurality of entities associated with an entity type, and on a grammar describing a plurality of phrase types, each of the plurality of phrase types associated with one or more conditions, and determination of a plurality of candidate queries based on the determined phrase types.

    Question Library For Data Analytics Interface

    公开(公告)号:US20210182291A1

    公开(公告)日:2021-06-17

    申请号:US16712760

    申请日:2019-12-12

    Abstract: A question library aids in intuitive analysis of stored data. The question library comprises: 1) a plurality of text questions, 2) a numerical representation (e.g., a vector) of each text question, and 3) a corresponding query in a query language. A numerical vector is generated for a question posed to a database. If a matching library question (based upon vector similarity) is not found, the user receives the original answer. If a matching library question based upon vector similarity is found, the user receives the answer to that library question (with potential modifications). Embodiments may determine similarity by calculating Pearson's coefficient, Spearman's rho, or Kendall's tau. Embodiments may parse the first query to identify constituent elements (measures, dimensions, filters). These entities are extracted and compared to elements of the second question matched within the library, to allow modification of the library query to align with the initial query.

    Question library for data analytics interface

    公开(公告)号:US11669523B2

    公开(公告)日:2023-06-06

    申请号:US16712760

    申请日:2019-12-12

    CPC classification number: G06F16/24522 G06F16/24553

    Abstract: A question library aids in intuitive analysis of stored data. The question library comprises: 1) a plurality of text questions, 2) a numerical representation (e.g., a vector) of each text question, and 3) a corresponding query in a query language. A numerical vector is generated for a question posed to a database. If a matching library question (based upon vector similarity) is not found, the user receives the original answer. If a matching library question based upon vector similarity is found, the user receives the answer to that library question (with potential modifications). Embodiments may determine similarity by calculating Pearson's coefficient, Spearman's rho, or Kendall's tau. Embodiments may parse the first query to identify constituent elements (measures, dimensions, filters). These entities are extracted and compared to elements of the second question matched within the library, to allow modification of the library query to align with the initial query.

    Auto-monitoring and adjustment of dynamic data visualizations

    公开(公告)号:US10324943B2

    公开(公告)日:2019-06-18

    申请号:US14822776

    申请日:2015-08-10

    Abstract: Examples of auto-monitoring and adjusting dynamic data visualizations are provided herein. A data visualization based on initial data can be generated. A series of data updates can be received. The data visualization can be updated based on the series of data updates. Various performance metrics can be monitored, and data updates and/or the updated data visualization can be adjusted accordingly. Performance metrics can include at least one of: a data visualization rendering time; a data transfer time; or a data update generation time. Upon determining that one or more performance metrics exceed a threshold: a time between data updates of the series of data updates can be increased; sampled data can be requested for subsequent data updates; and/or a time-dimension extent of the updated data visualization can be reduced.

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