王耀华;李舟军;何跃鹰;巢文涵;周建设. 基于文本语义离散度的自动作文评分关键技术研究[J]. 中文信息学报, 2016, 30(6): 173-181.
WANG Yaohua; LI Zhoujun; HE Yueying; CHAO Wenhan; ZHOU Jianshe. Research on Key Technology of Automatic Essay Scoring #br# Based on Text Semantic Dispersion. , 2016, 30(6): 173-181.
Research on Key Technology of Automatic Essay Scoring #br# Based on Text Semantic Dispersion
WANG Yaohua1; LI Zhoujun1; HE Yueying2; CHAO Wenhan1; ZHOU Jianshe3
1. School of Computer Science and Engineering, Beihang University, Beijing 100191, China;
2. National Computer Network Emergency Response Technical Team, Beijing 100029, China;
3. Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing 100048, China
Abstract:Based on the existing methods, including LDA model, paragraph vector, word vector text, we extract four kinds of text semantic dispersion representations, and apply them on the automatic essay scoring. This paper gives a vector form of the text semantic dispersion from the statistical point of view and gives a matrix form from the perspective of decentralized text semantic dispersion, experimented on the multiple linear regression, convolution neural network and recurrent neural network. The results showed that, on the test data of 50 essays, after the addition of text semantic dispersion feature, the Root Mean Square Error is reduced by 10.99% and the Pearson correlation coefficient increases 2.7 times.
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