使用机器学习对汉语评论进行情感分类

摘要

We solved the Chinese review sentiment classification problem via describing and evaluating several machine learning approaches ( Na(I)ve Bayes, maximum entropy and support vector machines) on some features of the Chinese reviews. The experiment shows the three machine learning methods perform well especially support vector machines, and the accuracy of sentence level is up to 88.26% , the accuracy of review level is up to 91.79%.%针对汉语评论的多种特征使用机器学习方法(如贝叶斯、最大熵和支持向量机), 解决了汉语评论的情感分类问题. 实验结果表明, 机器学习方法对汉语评论的分类效果较好, 支持向量机的表现最好. 句子级别和评论级别的准确率分别达到88.26%和91.79%.