GRANULAR DATA FOR BEHAVIORAL TARGETING

    公开(公告)号:US20170140424A9

    公开(公告)日:2017-05-18

    申请号:US13739400

    申请日:2013-01-11

    Applicant: YAHOO! INC.

    CPC classification number: G06Q30/0251 G06F17/00 G06N5/02

    Abstract: A method of targeting receives several granular events and preprocesses the received granular events thereby generating preprocessed data to facilitate construction of a model based on the granular events. The method generates a predictive model by using the preprocessed data. The predictive model is for determining a likelihood of a user action. The method trains the predictive model. A system for targeting includes granular events, a preprocessor for receiving the granular events, a model generator, and a model. The preprocessor has one or more modules for at least one of pruning, aggregation, clustering, and/or filtering. The model generator is for constructing a model based on the granular events, and the model is for determining a likelihood of a user action. The system of some embodiments further includes several users, a selector for selecting a particular set of users from among the several users, a trained model, and a scoring module.

    GRANULAR DATA FOR BEHAVIORAL TARGETING
    2.
    发明申请
    GRANULAR DATA FOR BEHAVIORAL TARGETING 有权
    用于行为目标的格式数据

    公开(公告)号:US20140200999A1

    公开(公告)日:2014-07-17

    申请号:US13739400

    申请日:2013-01-11

    Applicant: YAHOO! INC.

    CPC classification number: G06Q30/0251 G06F17/00 G06N5/02

    Abstract: A method of targeting receives several granular events and preprocesses the received granular events thereby generating preprocessed data to facilitate construction of a model based on the granular events. The method generates a predictive model by using the preprocessed data. The predictive model is for determining a likelihood of a user action. The method trains the predictive model. A system for targeting includes granular events, a preprocessor for receiving the granular events, a model generator, and a model. The preprocessor has one or more modules for at least one of pruning, aggregation, clustering, and/or filtering. The model generator is for constructing a model based on the granular events, and the model is for determining a likelihood of a user action. The system of some embodiments further includes several users, a selector for selecting a particular set of users from among the several users, a trained model, and a scoring module.

    Abstract translation: 定向的方法接收几个粒度事件并预处理所接收的粒状事件,从而生成预处理的数据,以便于基于粒状事件构建模型。 该方法通过使用预处理数据生成预测模型。 预测模型用于确定用户动作的可能性。 该方法训练预测模型。 用于定位的系统包括粒状事件,用于接收粒度事件的预处理器,模型生成器和模型。 预处理器具有一个或多个用于修剪,聚合,聚类和/或过滤中的至少一个的模块。 模型生成器用于基于粒度事件构建模型,模型用于确定用户操作的可能性。 一些实施例的系统还包括若干用户,用于从几个用户中选择特定用户组的选择器,训练模型和评分模块。

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