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Automatic Essay Scoring Based on Coh-Metrix Feature Selection for Chinese English Learners

机译:基于Coh-Metrix特征选择的中国英语学习者自动作文评分

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Automatic essay scoring can be based on essay's content or form. We believe that both classes of features can reflect some aspects of an essay's quality and they should be combined. In this paper, we use Coh-Metrix and importance measure to extract features that cover a wide range of features relating to the essay's grammatical structure, content, form, cohesion, and so on, and more related to the Chinese English Learners. This is a more complete set of features than those used in the literature and it is expected to better cover an essay's characteristics. SVM and C5.0 classification methods based on these features are used to predict the essay's score. Our experiments show that this set of features can produce good results on Chinese English essays even when we use top 5 and top 15 features with higher importance score.
机译:自动评分可以基于文章的内容或形式。我们认为,这两类功能都可以反映论文质量的某些方面,应该将它们结合起来。在本文中,我们使用Coh-Metrix和重要性度量来提取特征,这些特征涵盖了与论文的语法结构,内容,形式,衔接等等有关的广泛特征,而更多地与中国英语学习者有关。这是一组比文献中使用的功能更完整的功能,并且有望更好地覆盖论文的特征。基于这些功能的SVM和C5.0分类方法用于预测论文的分数。我们的实验表明,即使我们使用重要性得分较高的前5个和前15个功能,这套功能也可以在中文英语文章中产生良好的效果。

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