METHOD AND APPARATUS FOR MODELING A POPULATION TO PREDICT INDIVIDUAL BEHAVIOR USING LOCATION DATA FROM SOCIAL NETWORK MESSAGES
    1.
    发明申请
    METHOD AND APPARATUS FOR MODELING A POPULATION TO PREDICT INDIVIDUAL BEHAVIOR USING LOCATION DATA FROM SOCIAL NETWORK MESSAGES 审中-公开
    使用来自社会网络信息的位置数据建模人群预测个人行为的方法和装置

    公开(公告)号:US20150309962A1

    公开(公告)日:2015-10-29

    申请号:US14262391

    申请日:2014-04-25

    Abstract: A method, non-transitory computer readable medium, and apparatus for predicting a location behavior of at least one individual are disclosed. For example, the method receives a plurality of social networking messages having spatial location data and user identification information, filters the plurality of social networking messages to remove one or more of the plurality of social networking messages that are not related to mobility of a user to create a filtered plurality of social networking messages, creates a population model by applying a kernel density estimation to the filtered plurality of social networking messages, creates an individual model for each different user identification by applying the kernel density estimation to a subset of the filtered plurality of social networking messages for the each different user identification and generates a probability density function map that predicts the location behavior of the at least one individual.

    Abstract translation: 公开了一种用于预测至少一个人的位置行为的方法,非暂时计算机可读介质和装置。 例如,该方法接收具有空间位置数据和用户识别信息的多个社交网络消息,对多个社交网络消息进行过滤以去除与用户移动性无关的多个社交网络消息中的一个或多个 创建过滤的多个社交网络消息,通过将核密度估计应用于经筛选的多个社交网络消息来创建群体模型,通过将核密度估计应用于经滤波的多个社会网络消息的子集来为每个不同的用户标识创建个体模型 的用于每个不同用户标识的社交网络消息,并且生成预测所述至少一个人的位置行为的概率密度函数图。

Patent Agency Ranking