基于答案知识库的汉英翻译自动评分

Wei Wu, Li Li
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引用次数: 3

摘要

目前的汉英翻译自动评分方法主要分为两大类,一类是基于文本相似度的评分方法,另一类是基于自然语言过程的评分方法。两者都必须面对准确性的问题。本文通过分析当前汉英翻译自动评分方法的不足,提出了一种基于答案知识库的汉英翻译自动评分方法。通过对答案进行语义扩展等方法构建答案知识库。基于答案知识库对学生的答案进行自动评分,提高了答案知识库的适应性、灵活性和准确性。对比实验分析表明,该方法效果良好,精度明显提高。同时,该方法也适用于其他主观测试的自动评分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automated Chinese-English translation scoring based on answer knowledge base
The current automated Chinese-English translation scoring methods mainly fall into two categories: one is based on the text similarity and the other on Natural Language Process (NLP). Both of them have to face the problem in their accuracy. This paper proposed an automated Chinese-English translation scoring method based on answer knowledge base by analyzing the shortcomings of the current automated scoring methods of Chinese-English translation. Answer knowledge base is constructed by means of such methods as semantic expansion of the answers. Students' answers are automatically scored based on the answer knowledge base, which improves its adaptability, flexibility and accuracy. The analysis of contrast experiments indicates that the method can work well and its accuracy is obviously improved. Meanwhile, this method can also apply to the automated scoring in other subjective tests.
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