中文微博观点句识别及评价对象抽取方法

Recognition of Chinese Micro-blog sentiment polarity and extraction of opinion target

根据微博文本中句子的依存关系和情感词在依存关系中的位置来提取特征,将特征应用于最大熵模型来预测句子的情感倾向(褒义、贬义或中性)。并在此基础上,将词、词性和词在句法结构中的成分作为特征,训练条件随机场统计模型以此预测评价对象。实验结果表明,将句法依存关系作为特征应用到中文微博观点句识别中能够取得不错的效果,明显提高了中文微博观点句的识别率。

According to the dependency and emotional words in sentences,we extract features and apply these features to the maximum entropy model to predict the polarity of a sentence( positive,negative or neutral). Using words,part of speech and composition of syntactic structure as a feature to train CRF model and extract opinion target. Experimental results shows that recognition rate of Chinese M icro-blogging sentiment polarity are increased obviously.