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Automatically identifying and minimizing potentially indirect meanings in electronic communications

机译:自动识别和最小化电子通信中的潜在间接含义

摘要

A computer system evaluating an input segment of a communication, in parallel, by a baseline classification model trained with baseline passages indicating dictionary meaning and multiple generative sequence models each trained to classify a particular passage from among multiple indirect passages indicating usage with an indirect meaning, to receive a separate score from the baseline classification model and each of the generative sequence models, each separate score indicating a classification probability for the input segment. The computer system, responsive to one or more particular scores generated by one or more of the generative sequence models exceeding a baseline score generated by the baseline classification model summed with a tuning factor, flagging the input segment as having a potentially indirect meaning.
机译:一种计算机系统,通过用基线传播模型并行地评估通信的输入段,该基线分类模型用基线通道训练,指示字典含义和多个生成序列模型,每个培训用于对从指示使用间接含义的多个间接传播中分类特定段落的特定段落, 为了从基线分类模型和每个生成序列模型中获得单独的分数,每个单独的分数指示输入段的分类概率。 计算机系统,响应于由一个或多个产生的一个或多个生成序列模型产生的一个或多个特定分数超过由由调谐因子求和的基线分类模型产生的基线分数,将输入段标记为具有潜在间接含义。

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