Sentiment Classification Based on Random Process

摘要：

Sentiment classification has attracted increasing interest from Natural Language Processing. The goal of sentiment classification is to automatically identify whether a given piece of text expresses positive or negative opinion towards a topic of interest. We present the standpoint that uses a human model based on random process to determine text polarity classification. Experiment results showed that on movie review corpus, the human modeling approach has a relatively higher accuracy than that of SVTVls and Naive Bayes classifier.

关键词： natural language processing sentiment classification random process

作者: Jintao Mao Jian Zhu

作者单位: Beijing Institute of Technology Beijing, China China Youth University For political Sciences Beijing, China

会议类型: 国际会议

会议名称: 2012 International Conference on Computer Science and Electronic Engineering(2012 IEEE计算机科学与电子工程国际会议 ICCSEE 2012)

会议地点: 杭州

会议语种:英文

页码: 473-476

在线出版日期: 2012-03-23（万方平台首次上网日期，不代表论文的发表时间）