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首页> 外文会议>International Conference on Cybernetics and Information Technologies, Systems and Applications(CITSA2004) and 10th International Conference on Information Systems Analysis and Synthesis(ISAS2004) vol.1 >Automated Essay Assessment System Using Text Classification and Clustering Algorithms
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Automated Essay Assessment System Using Text Classification and Clustering Algorithms

机译：使用文本分类和聚类算法的自动论文评估系统

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摘要

Automated essay grading has been a topic of research since the early 1960s. It began as a simple system designed to automatically grade student essays. The idea was to alleviate the heavy demand placed on teachers to do such a task. For example, imagine the time and effort involved for a social studies teacher to grade eighty-two tests, each containing three essay answers. How long will the teacher spend grading the tests? How consistent will the grading be? The purpose of an automated essay assessment system is to classify essays according to their content. The classes A, B, C, D, and F correspond to an academic grade assigned by a teacher for each student written essay. These classes are rated from highest quality to lowest quality, respectively. Quality, for this purpose, will be determined by content. Clustering algorithms such as K-Means can be used to alleviate the grading tasks. This preliminary work shows related documents can be assigned to the same clusters to perhaps reduce the number of documents to be graded.
机译：自1960年代初以来，自动论文评分一直是研究的主题。它开始于一个简单的系统，旨在自动为学生的论文评分。这样做的目的是减轻教师对执行此类任务的沉重需求。例如，想象一下社会研究老师为八十二个测试打分所花费的时间和精力，每个测试包含三个作文答案。老师会花多长时间对考试进行评分？评分的一致性如何？自动化论文评估系统的目的是根据论文的内容对论文进行分类。 A，B，C，D和F类对应于老师为每位学生撰写的论文指定的学术等级。这些类别分别从最高质量到最低质量进行评级。为此，质量将取决于内容。诸如K-Means之类的聚类算法可用于减轻评分任务。这项初步工作表明，可以将相关文档分配给相同的类别，以减少要分级的文档数量。

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