计算机科学

计算机科学 ›› 2019, Vol. 46 ›› Issue (3): 234-241.doi: 10.11896/j.issn.1002-137X.2019.03.035

• 人工智能 • 上一篇    下一篇

基于篇章结构的英文作文自动评分方法

周明1,3,贾艳明2,周彩兰1,徐宁1,3   

  1. (武汉理工大学计算机科学与技术学院 武汉 430070)1
    (北京博智天下信息技术有限公司人工智能与大数据研究中心 北京 100085)2
    (武汉理工大学交通物联网技术湖北省重点实验室 武汉 430070)3
  • 收稿日期:2018-01-24 修回日期:2018-05-13 出版日期:2019-03-15 发布日期:2019-03-22
  • 通讯作者: 周彩兰(1964-),女,硕士,副教授,主要研究方向为深度学习、图像处理,E-mail:383277764@qq.com
  • 作者简介:周明(1993-),男,硕士生,主要研究方向为自然语言处理、篇章分析,E-mail:zhoum1118@163.com;贾艳明(1980-),男,博士,高级工程师,主要研究方向为机器学习、算法优化;徐宁(1968-),男,博士,教授,博士生导师,CCF高级会员,主要研究方向为超大规模集成电路的计算机辅助设计系统、计算机体系结构、数据挖掘和算法优化。

English Automated Essay Scoring Methods Based on Discourse Structure

ZHOU Ming1,3,JIA Yan-ming2,ZHOU Cai-lan1,XU Ning1,3   

  1. (School of Computer Science and Technology,Wuhan University of Technology,Wuhan 430070,China)1
    (Research Center for Artificial Intelligence and Big Data,Global Wisdom Inc,Beijing 100085,China)2
    (Hubei Key Laboratory of Transportation Internet of Things,Wuhan University of Technology,Wuhan 430070,China)3
  • Received:2018-01-24 Revised:2018-05-13 Online:2019-03-15 Published:2019-03-22

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摘要： 作文自动评分(Automated Essay Scoring AES)是指使用统计学、自然语言处理及语言学等领域的技术对作文进行评价和评分的系统。篇章结构分析是自然语言处理领域的一个重要研究方向,也是作文自动评分系统的重要组成部分之一。目前国外的作文自动评分系统虽有广泛应用,但对篇章结构评分的研究还存在不足,且对中国学生英语作文的针对性不强;国内对英语作文自动评分的研究处于起步阶段,忽视了篇章结构对英语作文评分的重要性。针对这些问题,提出一种基于篇章结构的英文作文自动评分方法,在词、句、段落3个层面上提取作文的词汇、句法以及结构等特征,并使用支持向量机、随机森林以及极端梯度上升等算法对篇章成分进行分类,最后构建线性回归模型对作文的篇章结构进行评分。实验结果表明,基于随机森林的篇章成分识别模型(Discourse Element Identification based Random Forest,DEI-RF)的准确率为94.13%;基于线性回归的篇章结构自动评分模型(Discourse Structures Scoring based Linear Regression,DSS-LR)在背景介绍段(Introduction)、论证段(Argumentation)以及让步段(Concession)的均方差可达到0.02,0.11和0.08。

关键词: 篇章成分, 篇章结构分析, 随机森林, 线性回归, 自然语言处理, 作文自动评分

Abstract: Automated essay scoring is defined as the computer technology that evaluates and scores the composition,based on the technologies of statistics,natural language processing,linguistics and some other fields.Discourse structure analysis is not only an important research field of natural language processing,but also an important component of the AES system.Nowadays,AES system has widely application.However,there is not enough research on the structure of the essay,and the AES system does not focus on the Chinese students.The domestic researches on the AES are in infancy,ignoring the importance of discourse structure in essay scoring.In view of these problems,this paper proposed a method of automated essay scoring based on discourse structure.Firstly,the method extracts essay’s features,such as vocabulary,lexical and discourse structure from levels of words,sentences and paragraphs.Then,the composition of essays is classified by support vector machines,random forests and extreme gradient boosting,and then the linear regression model with the discourse element is constructed to score the compositions.The experimental results show that the accuracy of discourse element identification based random forest (DEI-RF) can reach 94.13%,and the mean squared error of automated discourse structure scoring based on linear regression (DSS-LR) model can reach 0.02,0.11 and 0.08 on introduction,argumentation and concession respectively.

Key words: Automated essay scoring, Discourse element, Discourse structure analysis, Linear regression

第3期周 明, Natural language processing, Random forest, 等:基于篇章结构的英文作文自动评分方法

中图分类号: 

  • TP391.1
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