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A Multi-aspect Analysis of Automatic Essay Scoring for Brazilian Portuguese

机译:巴西葡萄牙语自动论文评分的多方面分析

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While several methods for automatic essay scoring (AES) for the English language have been proposed, systems for other languages are unusual. To this end, we propose in this paper a multi-aspect AES system for Brazilian Portuguese which we apply to a collection of essays, which human experts evaluated according to the five aspects defined by the Brazilian Government for the National High School Exam (ENEM). These aspects are skills that student must master and every skill is assessed separately from one another. In addition to prediction, we also performed feature analysis for each aspect. The proposed AES system employs several features already used by AES systems for the English language. Our results show that predictions for some aspects performed well with the employed features, while predictions for other aspects performed poorly. Furthermore, the detailed feature analysis we performed made it possible to note their independent impacts on each of the five aspects. Finally, aside from these contributions, our work reveals some challenges and directions for future research, related, for instance, to the fact that the ENEM has over eight million yearly enrollments.
机译:虽然已经提出了用于英语语言的几种用于自动论文评分(AES)的方法,但其他语言的系统是不寻常的。为此,我们向本文提出了一种用于巴西葡萄牙语的多个方面AES系统,我们适用于一系列论文,这些论文根据巴西政府为国家高中考试(enem)定义的五个方面进行评估的人类专家。这些方面是学生必须掌握的技能,每项技能都被彼此分开评估。除了预测外,我们还对每个方面进行了特征分析。拟议的AES系统采用AES系统用于英语语言的几个功能。我们的结果表明,对于某些方面的预测,对所采用的特征进行了很好地表现良好,而对其他方面的预测表现不佳。此外,我们执行的详细特征分析使得可以注意到其对五个方面中的每一个的独立影响。最后,除了这些贡献之外,我们的工作揭示了未来研究的一些挑战和方向,例如,与enem超过八千百万年份的入学事实。

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