【作者】 陆玉清； 洪宇； 陆军； 姚建民； 朱巧明；

【Author】 Yu-Qing Lu,Yu Hong,Jun Lu,Jian-Min Yao,Qiao-Min Zhu Provincial Key Laboratory of Computer Information Processing Technology Soochow University,Suzhou,China,215006

【机构】 苏州大学江苏省计算机信息处理重点实验室；

【摘要】 英文文本中的真词错误即输入的错词是和原词相似的另一个有效词。本文主要研究了对该类错误的检测。通过从所要检测的单词的上下文中提取句法和语义两个方面的特征,运用文档频率和信息增益进行特征筛选,实现了对上下文特征的有效提取。最终把判断该单词使用的正确与否看作分类问题,使用Winnow分类算法进行训练和测试。通过5阶交叉验证,所收集的61组混淆集的平均正确率与召回率分别为96%,79.47%。更多还原

【Abstract】 Context-dependent word errors in English texts are errors in which one correctly spelled word is substituted for another.This paper mainly discussed how to detect this type of errors.In the work reported here, we represent a method that firstly we extract features of syntax and semantics from the word context,and then we use Document Frequency and Information Gain to do feature selection,realizing the effective extraction of contextual features At last,we modeled the detecting task as a classification using the Winnow algorithm to train and test the sentences that are related with those confusion words.With five-across validation,the average precision and recall are respectively 96%,79.47%according to the 6lgroups of confusion sets.更多还原