基于局部和全局语义关联的英语文本语义分级模型

Guimin Huang, Shiwei Duan, Ya Zhou
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摘要

本文从不同角度提出了一种基于英语文本内容的语义分级模型。SGM不仅评估理想文本和被测文章之间的全局语义相关性,还考虑相邻文本段之间的局部语义相关性,以及不同文本段之间和整个文本之间的语义关系。将局部语义关联和全局语义关联结合起来,在语义的基础上衡量文本内容的整体质量。我们的实验表明,SGM能够在语义分级方面评估英语文本的内容。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A semantic grading model integrated local and global semantic relatedness for English text
This paper proposed a semantic grading model (SGM) for English text based on its content in different views. The SGM not only assesses the global semantic relatedness between ideal text and tested essay, local semantic relatedness between adjoining text segments, as well as the semantic relationship between vary text segments and the whole texts are also taken into account. Local and global semantic relatedness are combined to measure the overall quality of text contents on the basis of semantic. Our experiment shows that the SGM is competent in assessing the content of English text in terms of semantic grading.
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