中文摘要：

作文跑题检测是作文自动评分系统的重要模块。传统的作文跑题检测一般计算文章内容相关性作为得分,并将其与某一固定阈值进行对比,从而判断文章是否跑题。但是实际上文章得分高低与题目有直接关系,发散性题目和非发散性题目的文章得分有明显差异,所以很难用一个固定阈值来判断所有文章。该文提出一种作文跑题检测方法,基于文档发散度的作文跑题检测方法。该方法的创新之处在于研究文章集合发散度的概念,建立发散度与跑题阈值的关系模型,对于不同的题目动态选取不同的跑题阈值。该文构建了一套跑题检测系统,并在一个真实的数据集中进行测试。实验结果表明基于文档发散度的作文跑题检测系统能有效识别跑题作文。

英文摘要：

Off-topic detection is important in the automated essay scoring systems. Traditional methods compute similarity between essays and then compare the similarity with a fixed threshold to tell whether the essay is off-topic. In fact, the essay score is heavily dependent on the type of topic, e.g. the essay score for divergent topic ranges very different from that of non-divergent topic. This prevents fixed threshold to identify off-topic for all essays. This paper proposes a new method of off-topic detection based on divergence of essays. We study the divergence of essays, and establish the linear regression model between divergence and threshold. Our method is featured by a dynamic threshold for each topic. Experimental results show that our method is more effective than baseline systems.