公开(公告)号：US20160165277A1

公开(公告)日：2016-06-09

申请号：US13843683

申请日：2013-03-15

Applicant: Google Inc.

Inventor： Roman Kirillov ,  Nicolas Remy ,  James Robert Koehler ,  Simon Michael Rowe ,  Xiaojing Wang ,  Diane Lambert

IPC: H04N21/24

CPC classification number: H04N21/251 ,  H04N21/25883 ,  H04N21/25891 ,  H04N21/44222

Abstract: A method, executed by a processor, for estimating media metrics from large population data includes formatting and storing panel data, the panel data comprising observed viewing data of a plurality of individual panelists and demographic data for the plurality of panelists, the panel being drawn from a large population; accessing the large population data, the large population data comprising household-level viewing data and household level demographics; training a model to estimate viewing audience size based on the observed panel data; estimating, using the trained model, audience size for each household in the large population data; estimating a viewing score for each individual viewer in a plurality of households in the large population data; and combining the estimates of audience size and viewing score to produce probabilities that each of the viewers in the household viewed a specific media event.

Abstract translation: 由处理器执行的用于从大量数据估计媒体度量的方法包括格式化和存储面板数据，面板数据包括多个单独小组成员的观察数据和多个小组成员的人口统计数据，面板从 人口众多 获取大量人口数据，大量人口数据包括家庭层面的观看数据和家庭层面的人口统计; 培训模型以根据观察到的面板数据估计观众人数; 在大量人口数据中，使用受过训练的模型估计每个家庭的受众人数; 估计大群体数据中多个家庭中每个单独观众的观看分数; 并且将观众大小和观看分数的估计结合起来，以产生每个家庭观众观看特定媒体事件的概率。