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    • 1. 发明申请
    • Method and System for Generating A Linear Machine Learning Model for Predicting Online User Input Actions
    • 用于生成用于预测在线用户输入操作的线性机器学习模型的方法和系统
    • US20110131160A1
    • 2011-06-02
    • US13018303
    • 2011-01-31
    • John CannyShi ZhongScott GaffneyChad BrowerPavel BerkhinGeorge H. John
    • John CannyShi ZhongScott GaffneyChad BrowerPavel BerkhinGeorge H. John
    • G06F15/18
    • G06Q30/02
    • 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.
    • 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。
    • 2. 发明授权
    • Granular data for behavioral targeting using predictive models
    • 使用预测模型的行为定位的粒度数据
    • US07921069B2
    • 2011-04-05
    • US11770413
    • 2007-06-28
    • John CannyShi ZhongScott GaffneyChad BrowerPavel BerkhinGeorge H. John
    • John CannyShi ZhongScott GaffneyChad BrowerPavel BerkhinGeorge H. John
    • G06F17/00G06N5/02
    • G06Q30/02
    • 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 pre-processed data. The predictive model is for determining a likelihood of a user action. The method trains the predictive mode. 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.
    • 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。 该方法训练预测模式。 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。
    • 3. 发明授权
    • Method and system for generating a linear machine learning model for predicting online user input actions
    • 用于生成用于预测在线用户输入动作的线性机器学习模型的方法和系统
    • US08364627B2
    • 2013-01-29
    • US13018303
    • 2011-01-31
    • John CannyShi ZhongScott GaffneyChad BrowerPavel BerkhinGeorge H. John
    • John CannyShi ZhongScott GaffneyChad BrowerPavel BerkhinGeorge H. John
    • G06F17/00G06N5/02
    • G06Q30/02
    • 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.
    • 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。
    • 4. 发明申请
    • Granular Data for Behavioral Targeting
    • 行为定位的粒度数据
    • US20090006363A1
    • 2009-01-01
    • US11770413
    • 2007-06-28
    • John CannyShi ZhongScott GaffneyChad BrowerPavel BerkhinGeorge H. John
    • John CannyShi ZhongScott GaffneyChad BrowerPavel BerkhinGeorge H. John
    • G06F17/30
    • G06Q30/02
    • 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 pre-processed data. The predictive model is for determining a likelihood of a user action. The method trains the predictive mode. 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.
    • 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。 该方法训练预测模式。 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。
    • 7. 发明申请
    • DISPLAY TIME OF A WEB PAGE
    • WEB页面的显示时间
    • US20140281858A1
    • 2014-09-18
    • US13843433
    • 2013-03-15
    • Xing YiJean-Marc LangloisScott Gaffney
    • Xing YiJean-Marc LangloisScott Gaffney
    • G06F17/22
    • G06F17/2247G06F9/44521G06F17/2235G06Q30/0277
    • A method for determining a display time of a page is provided, including the following method operations: receiving a request for page data from a client; in response to the request, sending the page data to the client, the page data defining a page when rendered by the client, the rendered page including a page event module configured to detect and log events in a beacon for transmission, the events being selected from a group comprising a page unhide event, a page hide event, and a page unload event; receiving the beacon from the client; reading events logged in the beacon; and determining a display time of the page based on the events logged in the beacon.
    • 提供了一种用于确定页面的显示时间的方法,包括以下方法操作:从客户端接收页面数据的请求; 响应于该请求,将页面数据发送给客户端,页面数据在由客户端呈现时定义页面,所呈现的页面包括被配置为检测和记录用于发送的信标中的事件的页面事件模块,所选择的事件 来自包括页面未隐藏事件,页面隐藏事件和页面卸载事件的组; 从客户端接收信标; 阅读在信标中记录的事件; 以及基于登录在所述信标中的事件来确定所述页面的显示时间。
    • 8. 发明申请
    • PAGE PERSONALIZATION BASED ON ARTICLE DISPLAY TIME
    • 基于文章显示时间的页面个性化
    • US20140279043A1
    • 2014-09-18
    • US13843504
    • 2013-03-15
    • Xing YiScott GaffneyJean-Marc Langlois
    • Xing YiScott GaffneyJean-Marc Langlois
    • G06F17/22G06Q30/02
    • G06F17/2247G06F16/972G06Q30/0269
    • A method for page personalization is provided, including the following method operations: identifying a user operating a client; receiving a request for page data from the client; determining a user profile associated with the user; for each of a plurality of articles, predicting a display time of the article when presented to the user, based on the user profile and features of the article; determining selected articles from the plurality of articles based on the predicted display times; assembling the page data, the page data defining a page when rendered by the client, the rendered page defining references to the selected articles; sending the page data to the client; wherein the method is executed by a processor
    • 提供了一种用于页面个性化的方法,包括以下方法操作:识别操作客户端的用户; 从客户端接收页面数据请求; 确定与所述用户相关联的用户简档; 对于多个物品中的每一个,基于用户简档和物品的特征,预测当呈现给用户时物品的显示时间; 基于预测的显示时间来确定来自所述多个物品的选定物品; 组合页面数据,当由客户端呈现时定义页面的页面数据,呈现的页面定义对所选择的文章的引用; 将页面数据发送给客户端; 其中所述方法由处理器执行