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Using Argument Mining to Assess the Argumentation Quality of Essays

机译:使用论证挖掘来评估论文的论证质量

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Argument mining aims to determine the argumentative structure of texts. Although it is said to be crucial for future applications such as writing support systems, the benefit of its output has rarely been evaluated. This paper puts the analysis of the output into the focus. In particular, we investigate to what extent the mined structure can be leveraged to assess the argumentation quality of persuasive essays. We find insightful statistical patterns in the structure of essays. From these, we derive novel features that we evaluate in four argumentation-related essay scoring tasks. Our results reveal the benefit of argument mining for assessing argumentation quality. Among others, we improve the state of the art in scoring an essay's organization and its argument strength.
机译:论证挖掘旨在确定文本的论证结构。尽管据说它对于将来的应用程序(例如书写支持系统)至关重要,但很少评估其输出的好处。本文将对输出的分析作为重点。特别是,我们研究了在何种程度上可以利用挖掘的结构来评估说服性论文的论证质量。我们在论文的结构中发现了有见地的统计模式。从这些中,我们得出了新颖的特征,可以在四个与论证相关的论文评分任务中进行评估。我们的结果揭示了论点挖掘对评估论点质量的好处。除其他外,我们在对论文的组织及其论证力进行评分时,提高了最新技术水平。

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