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MACHINE LEARNING TECHNIQUES FOR ANALYZING TEXTUAL CONTENT

机译:用于分析文本内容的机器学习技术

摘要

Techniques are provided for using machine learning techniques to analyze textual content. In one technique, a potential item is identified within a document. An analysis of the potential item is performed at multiple levels of granularity that includes two or more of a sentence level, a segment level, or a document level. The analysis produces multiple outputs, one for each level of granularity in the multiple levels of granularity. The outputs are input into a machine-learned model to generate a score for the potential item. Based on the score, the potential item is presented on a computing device. In response to user selection of the potential item, an association between the potential item and the document is created. The association may be used later to identify a set of users to which the document (or data thereof) is to be presented.
机译:提供了使用机器学习技术来分析文本内容的技术。在一种技术中,在文档中识别潜在项目。对潜在项目的分析是在多个粒度的粒度下进行的,该粒度包括两个或更多个句子级别,段级别或文档级别。分析产生多个输出,一个用于多个粒度粒度的每个粒度。输出输入到机器学习模型中以为潜在项目生成分数。基于分数,潜在的项目呈现在计算设备上。响应于用户选择潜在项目,创建潜在项目与文档之间的关联。稍后可以使用该关联以识别要呈现的一组用户(或其数据)的用户。

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