An Approach to Analyzing Subjective Text Based on Feature Selection Algorithm

摘要：

This paper proposed a method to analyzing subjective text. The method uses various strategies to stand for text with feature vectors, and uses SVM to classify text according to the property of subjectivity and objectivity after eliminating the rundant and irrelevant features using feature selection algorithm. The feature selection algorithm in the paper bases on S1MBA. We improve the original SIMBA on the way of iteration and the measure of similarity through experiment, and overcome the instability when putting into application. In the experiment done on theTREC evaluation corpus, the accuracy overperforms that by SVM algorithm alone and the F-MEASlRE is better then that by the baseline method in same corpus.

关键词： opinion mining sentiment analysis subjectivity analysis feature selection

作者: Tian Weixin Zheng Sheng

作者单位: College of Computer and Information Technology, Three Gorges University, YiChang, 443000, China College of Science, China Three Gorges University, YiChang, 443000, China

会议类型: 国际会议

会议名称: 2010 International Conference on Circuit and Signal Processing(2010年电路与信号处理国际会议 ICCSP 2010)

会议地点: 上海

会议语种:英文

页码: 663-667

在线出版日期: 2010-12-25（万方平台首次上网日期，不代表论文的发表时间）