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APPLYING A TRAINED MODEL FOR PREDICTING QUALITY OF A CONTENT ITEM ALONG A GRADUATED SCALE

机译:应用训练模型来预测渐进规模中内容项的质量

摘要

An online system receives a request to present a content item to a viewing user who is associated with a set of user attributes. The online system retrieves a regression model for predicting an expected quality for a particular content item and a particular set of users attributes. The regression model was trained, using machine learning, based on user-assigned quality scores, each corresponding to a content item and provided by a quality-assigning user, and sets of user attributes, each set associated with one of the quality-assigning users. The online system uses the regression model to predict a quality score, indicating the quality of a content item to the viewing user, based on the set of user attributes that is associated with the viewing user. The online system determines to provide the content to the viewing user based on the quality score, and transmits the content item to the viewing user.
机译:在线系统接收向与一组用户属性相关联的观看用户呈现内容项的请求。在线系统检索用于预测特定内容项和特定用户属性集的预期质量的回归模型。使用机器学习,基于用户分配的质量得分对回归模型进行训练,每个质量得分对应于一个内容项并由质量分配用户提供,以及用户属性集,每个属性集与其中一个质量分配用户相关联。在线系统基于与观看用户相关联的用户属性集合,使用回归模型来预测质量得分,该质量得分向观看用户指示内容项的质量。在线系统基于质量得分确定将内容提供给观看用户,并将内容项发送给观看用户。

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