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Utilizing a machine learning model to predict performance and generate improved digital design assets

机译:利用机器学习模型预测性能并生成改进的数字设计资产

摘要

Methods, systems, and computer readable storage media for improving predictive analytics for performance of digital design assets. In particular, one or more embodiments train a machine-learning model based on previously used digital design assets. One or more embodiments use the machine-learning model to analyze attributes of a user-generated digital design asset to generate an asset score that predicts the performance of the user-generated digital design asset for a target audience segment. One or more embodiments also use the machine-learning model to generate attribute scores for the attributes, and then generate the asset score based on the attribute scores. Additionally, one or more embodiments then provide the asset score to a user (e.g., a content creator) within an asset creation application to allow the user to improve the digital design asset for use in one or more digital content campaigns directed to the target audience segment.
机译:用于改进数字设计资产性能的预测分析的方法,系统和计算机可读存储介质。特别地,一个或多个实施例基于先前使用的数字设计资产来训练机器学习模型。一个或多个实施例使用机器学习模型来分析用户生成的数字设计资产的属性,以生成资产分数,该资产分数预测用户生成的数字设计资产对于目标受众的表现。一个或多个实施例还使用机器学习模型来生成属性的属性分数,然后基于属性分数来生成资产分数。另外,一个或多个实施例然后在资产创建应用程序中向用户(例如,内容创建者)提供资产分数,以允许用户改进数字设计资产以用于针对目标受众的一个或多个数字内容活动中分割。

著录项

  • 公开/公告号US10789610B2

    专利类型

  • 公开/公告日2020-09-29

    原文格式PDF

  • 申请/专利权人 ADOBE INC.;

    申请/专利号US201715699156

  • 发明设计人 KEVIN SMITH;

    申请日2017-09-08

  • 分类号G06Q30/02;G06N7;G06N5/02;G06N20;

  • 国家 US

  • 入库时间 2022-08-21 11:29:23

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