首页> 外国专利> Evaluating content for compliance with a content policy enforced by an online system using a machine learning model determining compliance with another content policy

Evaluating content for compliance with a content policy enforced by an online system using a machine learning model determining compliance with another content policy

机译:评估内容遵守由在线系统使用的机器学习模型确定符合其他内容策略的内容策略的内容策略

摘要

An online system maintains machine learning models that determine risk scores for content items indicating likelihoods of content items violating content policies associated with the machine learning models. When the online system obtains an additional content policy, the online system applies a maintained machine learning model to a set including content items previously identified as violating or not violating the additional content policy. The online system maps the risk scores determined for content items of the set to likelihoods of violating the additional content policy based on the identifications of content times in the set violating or not violating the additional content policy. Subsequently, the online system applies the maintained machine learning model to content items and determines likelihoods of the content items violating the additional content policy based on the mapping of risk scores to likelihood of violating the additional content policy.
机译:在线系统维护机器学习模型,用于确定内容项的风险分数,指示违反了与机器学习模型相关联的内容策略的内容项的可能性。当在线系统获得额外的内容策略时,在线系统将维护的机器学习模型应用于包括先前被标识为违反其他内容策略的内容项的集合。在线系统地图确定设置的内容项的风险分数到基于集合中的内容时间的标识违反附加内容策略的可能性,或者不会违反其他内容策略。随后,在线系统将维护的机器学习模型应用于内容项,并基于风险得分的映射到违反附加内容策略的可能性,确定内容项的似然项违反了附加内容策略。

著录项

  • 公开/公告号US11023823B2

    专利类型

  • 公开/公告日2021-06-01

    原文格式PDF

  • 申请/专利权人 FACEBOOK INC.;

    申请/专利号US201715449448

  • 发明设计人 EMANUEL ALEXANDRE STRAUSS;

    申请日2017-03-03

  • 分类号G06N20;G06Q30/02;G06Q50;G06N7;

  • 国家 US

  • 入库时间 2022-08-24 19:03:38

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