CONTRIBUTION INCREMENTALITY MACHINE LEARNING MODELS

• Main Authors: RICHARDSON AMY, JIAO YANG, NASIRI AMINI ALI, WANG JINSONG, TAKAGI JUNJI, ZHANG YAN, SHENDER DINAH, ZHANG ZHILIU, JIANG RUOYI, DIKMEN MERT, LEE SHAOYING, BAO XINLONG
• Format: Patent
• Language: Chinese; English
• Published: 14.12.2021
• Subjects: CALCULATING; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

Methods, systems, and computer programs encoded on a computer storage medium, for training and using machine learning models are disclosed. Methods include creating a model that represents relationships between user attributes, content exposures, and performance levels for a target action using organic exposure data specifying one or more organic exposures experienced by a particular user over a specified time prior to performance of a target action by the particular user and third party exposure data specifying third party exposures of a specified type of digital component to the particular user over the specified time period. Using the model, an incremental performance level attributable to each of the third party exposures at an action time when the target action was performed by the particular user is determined. Transmission criteria for at least some digital components to which the particular user was exposed are modified based on the incremental performance. 公开了用于训练和使用机器学习模型的方法、系统和编码在计算机存储介质上的计算机程序。方法包