少数民族汉语考试的作文辅助评分系统研究  

Research on Assisted Scoring System for Chinese Proficiency Test for Minorities

作　　者：蔡黎[1] 彭星源[1] 赵军[1] 

机构地区：[1]中国科学院自动化研究所模式识别国家重点实验室,北京100190

出　　处：《中文信息学报》2011年第5期120-126,共7页Journal of Chinese Information Processing

基　　金：国家自然科学基金资助项目(60875041;61070106);国家自然科学基金青年基金资助项目(61103152)

摘　　要：随着计算机的普遍应用以及计算机技术的快速发展,计算机辅助性测试和计算机自适应性测试都已先后成为现实。计算机辅助评分,也称作计算机自动评分,就成为人们所希望的下一代计算机辅助工具。中文辅助评分系统的研究尚处于起步阶段,据我们了解还没有一个能大规模使用的系统。我们研究了许多英文的辅助评分系统,并按照文章中的算法提取特征,但是特征的相关度并不高。在该文中,我们利用统计自然语言处理和信息检索的技术提取作文写作水平和作文主题特征。在建模时,融入样本分数分布和一位评分员的评分的信息,创造性的提出三重分段回归模型。实验表明,利用我们的辅助评分系统协助评分,在节省一半阅卷量的情况下,精度可以达到97%以上。With the widespread application of computer and fast development of computer techonlogy,computer aided test and computer adopted test have turned into realization.Assisted essay scoring system（AES） have become the next generation of computer aided tools in people＇s expectation.Chinese AES is still in its infant stage.As we know that there is even no Chinese AES which can be widely used.We have done a lot of research on English AES.And we extracted some features described in the paper.However,the result was not promising.In this paper,we use the technology of statistical natural language processing and information retrieval to extract features.Then,we creatively integrate features such as the distribution of sample test score and a reviewer＇s score into statistical model,which we call triple segmented regression.The result is tremendous good.The experiment shows that using our AES,we can only use half of the labour force to get the precision above 97%.

关 键 词：作文辅助评分 汉语 主题特征 写作水平特征 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]