使用自然语言处理和文本挖掘方法的自动作文评分

Gunawansyah, R. Rahayu, Nurwathi, B. Sugiarto, Gunawan
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引用次数: 7

摘要

技术的使用确实有助于最大限度地提高工作的有效性和效率,特别是在教育领域。电子学习是在本次covid-19大流行中开始广泛实施的教育概念,以避免通过社交距离传播。其中一种电子学习类型是论文,但对于大型参与者来说,人工评估需要花费很多精力。评价员由于疲劳导致的评价不一致也会影响评价的质量。使用机器学习和计算语言学来研究计算机与人类自然语言之间的相互作用,使用本研究中提出的自然语言处理来开发一个无需人类反复编程即可自行学习和理解的系统。自然语言处理和文本挖掘方法能够提供良好的评估,而评估受几个过程的影响,即标记化、停止词、词干提取和关键词数量支持,以及更复杂的关键词的同义词。自动论文评分系统被证明可以提供一致和客观的评估,并且能够接近人类评分者的评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automated Essay Scoring Using Natural Language Processing And Text Mining Method
The use of technology really helps to maximized the effectiveness and efficiency of work expecially in the education field. Elearning is the concept of education that has begun to be widely implemented at this covid-19 pandemic to avoid the spread of transmission through social distancing. One of elearning types is essay but for large participants, it need much effort for evaluate by human rater. The inconsistency of assessment by the rater due to fatigue can also affect the quality of the assessment. Developing a system that can learn and understand on its own without having to be repeatedly programmed by humans used machine learning and computational linguistics to study the interaction between computers and human natural language used natural language processing proposed in this research. Natural language processing and text mining methods are able to provide a good assessment which is influenced by several processes, namely tokenization, stopword, stemming and support with the number of keywords, and the synonym of more complex keywords. The automated essay scoring system is proven to provide consistent and objective assessments and is able to approach human raters assessments.
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