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    SYSTEMS AND METHODS FOR REDUCING DATA COLLECTION BURDEN
    2.
    发明申请
    SYSTEMS AND METHODS FOR REDUCING DATA COLLECTION BURDEN 有权

    公开(公告)号：US20220075763A1

    公开(公告)日：2022-03-10

    申请号：US17466738

    申请日：2021-09-03

    申请人： The MITRE Corporation

    发明人： Leslie David SERVI ,  Randy Clinton PAFFENROTH ,  Melanie Ann JUTRAS ,  Deon Lamar BURCHETT

    IPC分类号： G06F16/215 ,  G06K9/62 ,  G06N5/04

    摘要： A system for reducing data collection burden, comprising: one or more programs including instructions for: receiving a first set of metrics for a plurality of facilities; receiving data associated with the first set of metrics from one or more facilities of the plurality of facilities; determining one or more anomalies in the received data; removing the determined one or more anomalies from the received data; selecting a second set of metrics from the first set of metrics, wherein a number of metrics of the second set is less than a number of metrics of the first set of metrics; and outputting a recommendation applicable to the plurality of facilities based on the second set of metrics.

    Identifying and Forecasting Shifts in the Mood of Social Media Users
    3.
    发明申请
    Identifying and Forecasting Shifts in the Mood of Social Media Users 有权
    识别和预测社交媒体用户心情的变化

    公开(公告)号：US20130275352A1

    公开(公告)日：2013-10-17

    申请号：US13750230

    申请日：2013-01-25

    申请人： THE MITRE CORPORATION

    发明人： Leslie David SERVI ,  Sara Beth ElSON

    IPC分类号： G06N3/08

    CPC分类号： G06N3/08 ,  G06Q10/00

    摘要： Quantitatively identifying and forecasting shifts in a mood of social media users is described. An example method includes categorizing the textual messages generated from the social media users over a selected period of time into a plurality of word categories, with each word category containing a set of words associated with the mood of social media users. A score indicating an intensity of the mood of the social media users is calculated for each word category, wherein a value of the score and its corresponding time point define a data point for the word category. Subsequently, breakpoints in the mood of social media users are determined so that the breakpoints minimize a sum of square errors representing a measurement of a consistency of all data points from inferred values of the scores of the data points derived using the breakpoints over the selected period of time. Further, space of all possible breakpoints for the word categories are searched to identify a defined number and locations of the breakpoints. Finally the breakpoints over the selected period of time are interpreted to identify the shifts in the mood of social media users and trends between breakpoints.

    摘要翻译： 描述了定量识别和预测社交媒体用户心情的转变。 示例性方法包括将从社交媒体用户生成的文本消息在所选择的时间段内分类成多个单词类别，每个单词类别包含与社交媒体用户的心情相关联的一组单词。 针对每个单词类别计算表示社交媒体用户的情绪强度的分数，其中分数的值和其对应的时间点定义单词分类的数据点。 随后，确定社交媒体用户的情绪中的断点，使得断点使用在所选择的周期内使用断点导出的数据点的得分的推断值来减少表示所有数据点的一致性的一致性的平方误差的和 的时间。 此外，搜索单词类别的所有可能断点的空间以识别断点的定义数量和位置。 最后，选择的时间段的断点被解释为识别社交媒体用户情绪的转变和断点之间的趋势。