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Automatic summarization assessment through a combination of semantic and syntactic information for intelligent educational systems

机译：通过语义和句法信息相结合的自动摘要评估，用于智能教育系统

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摘要

Summary writing is a process for creating a short version of a source text. It can be used as a measure of understanding. As grading students' summaries is a very time-consuming task, computer-assisted assessment can help teachers perform the grading more effectively. Several techniques, such as BLEU, ROUGE, N-gram co-occurrence, Latent Semantic Analysis (LSA), LSA_Ngram and LSA_ERB, have been proposed to support the automatic assessment of students' summaries. Since these techniques are more suitable for long texts, their performance is not satisfactory for the evaluation of short summaries. This paper proposes a specialized method that works well in assessing short summaries. Our proposed method integrates the semantic relations between words, and their syntactic composition. As a result, the proposed method is able to obtain high accuracy and improve the performance compared with the current techniques. Experiments have displayed that it is to be preferred over the existing techniques. A summary evaluation system based on the proposed method has also been developed.
机译：摘要编写是用于创建源文本的简短版本的过程。它可以用作理解的一种手段。由于对学生的摘要进行评分是一项非常耗时的任务，因此计算机辅助评估可以帮助教师更有效地进行评分。为了支持对学生摘要的自动评估，已经提出了几种技术，例如BLEU，ROUGE，N-gram共现，潜在语义分析（LSA），LSA_Ngram和LSA_ERB。由于这些技术更适合于长篇文章，因此其性能对于简短摘要的评估并不令人满意。本文提出了一种适用于评估简短摘要的特殊方法。我们提出的方法整合了单词之间的语义关系及其句法组成。结果，与现有技术相比，所提出的方法能够获得高精度并改善性能。实验表明，它优于现有技术。还开发了基于所提出方法的简要评估系统。

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