Automated Essay Scoring Using Incremental Latent Semantic Analysis
Automated Essay Scoring Using Incremental Latent Semantic Analysis
复制标题
使用增量潜在语义分析进行自动论文评分
DOI：
10.4304/jsw.9.2.429-436
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发表时间：
2014-01
期刊：
影响因子：
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通讯作者：
Hengli Peng
中科院分区：
文献类型：
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作者：
Mingqing Zhang;Shudong Hao;Yanyan Xu;Dengfeng Ke;Hengli Peng
Writing has been increasingly regarded by the testers of language tests as an important indicator to assess the language skill of testees. As such tests become more and more popular and the number of testees becomes larger, it is a huge task to score so many essays by raters. So far, many methods have been used to solve this problem and the traditional method is Latent Semantic Analysis (LSA). In this paper, we introduce a new incremental method of LSA to score essays effectively when the dataset is massive. By comparison of the traditional method and our new incremental method, concerning the running time and memory usage, experimental results make it obvious that the incremental method has a huge advantage over the traditional method. Furthermore, we use real corpora of test essays submitted to the MHK test (Chinese Proficiency Test for Minorities), to demonstrate that the incremental method is not only efficient but also effective in performing LSA. The experimental results also show that when using incremental LSA, the scoring accuracy can reach 88.8%.
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DOI：
10.1137/1.9781611972733.4
发表时间：
2003
期刊：
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作者：
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通讯作者：
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DOI：
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发表时间：
2006-04
期刊：
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发表时间：
2002-12
期刊：
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作者：
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DOI：
10.1007/978-3-642-20998-7_60
发表时间：
2011-04
期刊：
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作者：
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通讯作者：
Surayati Ismail;R. Othman;S. Kasim
DOI：
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发表时间：
2001
期刊：
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作者：
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通讯作者：
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