Opinion analysis based on a fusion of multiple classifiers approach
Bing Xu, Tiejun Zhao, Dequan Zheng, Qingxuan Chen · 2009
With the rapid expansion of network application, more and more customer reviews are available online. In this paper, A method for opinion analysis based on the fusion of multiple classifiers was presented, reliability function was introduced to select the text that is hard to determine by the main classifier, for these texts, multiple classifiers were used to determine which category the unlabeled documents belong to by voting. Experiments showed that the performance of text classification was improved by the proposed method. Compared with single classifier, this method achieved better performance, only increasing a small amount of time than using single main classifier.