首页> 外国专利> UTILIZING MACHINE LEARNING FROM EXPOSED AND NON-EXPOSED USER RECALL TO IMPROVE DIGITAL CONTENT DISTRIBUTION

UTILIZING MACHINE LEARNING FROM EXPOSED AND NON-EXPOSED USER RECALL TO IMPROVE DIGITAL CONTENT DISTRIBUTION

机译:利用已曝光和未曝光用户的机器学习提示来改善数字内容分配

摘要

One or more embodiments of the present disclosure involve training and utilizing a recall machine learning model to predict recall lift on a per-user basis with respect to digital content items. For example, systems described herein train a recall machine learning model based on poll responses from exposed users and non-exposed users with regard to sample digital content. In particular, the systems described herein train the recall machine learning model to output recall lift scores for a target user based on an assumption that the target user has been exposed to digital content and an assumption that the target user has not been exposed to the digital content. The systems described herein further involve delivering digital content in accordance with the recall lift score.
机译:本公开的一个或多个实施例涉及训练和利用召回机器学习模型以针对数字内容项在每个用户的基础上预测召回提升。例如,本文所述的系统基于关于样本数字内容的来自暴露用户和未暴露用户的轮询响应来训练召回机器学习模型。特别地,本文所述的系统基于目标用户已经暴露于数字内容的假设和目标用户尚未暴露于数字的假设来训练召回机器学习模型以输出目标用户的召回提升分数。内容。本文描述的系统还涉及根据召回提升分数来递送数字内容。

著录项

相似文献

  • 专利
  • 外文文献
  • 中文文献
获取专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号