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首页> 外文会议>2017 Intl Conf on Advanced Control Circuits Systems amp; 2017 Intl Conf on New Paradigms in Electronics amp; Information Technology >Automated essay scoring linguistic feature: Comparative study
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Automated essay scoring linguistic feature: Comparative study

机译：论文自动评分的语言特征：比较研究

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摘要

Automated Essay Scoring (AES) is the solution to a tedious and time consuming activity of manually scoring students' essays. AES is usually treated as a supervised machine learning problem where feature extraction plays an important role. In an attempt to investigate the importance of lexical features in AES systems, a new extended feature set is developed by combining popularly known features. The combinedfeature set contains 22 features that captures five different aspects of writing qualities. The importance of each feature in the combined feature set is tested by eliminating each feature separately. It was found that using the number of nouns in the essay slightly degrades the AES system performance. The significance of the combined feature set is compared against three state-of-the-art AES commercial systems and its performance was found comparable.
机译：自动作文评分（AES）是对学生的论文进行人工评分的乏味且耗时的活动的解决方案。 AES通常被视为有监督的机器学习问题，其中特征提取起着重要的作用。为了研究词法特征在AES系统中的重要性，通过结合众所周知的特征开发了新的扩展特征集。组合功能集包含22个功能，这些功能捕获了写作质量的五个不同方面。通过分别消除每个功能来测试组合功能集中每个功能的重要性。发现在论文中使用名词数量会稍微降低AES系统的性能。将组合功能集的重要性与三个最新的AES商业系统进行了比较，发现其性能相当。

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