A Clustering-based Approach on Sentiment Analysis

摘要：

This paper introduces the clustering-based sentiment analysis approach which is a new approach to sentiment analysis. By applying a TF-IDF weighting method, voting mechanism and importing term scores, an acceptable and stable clustering result can be obtained. It has competitive advantages over the two existing kinds of approaches: symbolic techniques and supervised learning methods. It is a well performed, efficient, and non-human participating approach on solving sentiment analysis problems.

作者: Gang Li Fei Liu

作者单位: Department of Computer Science and Computer Engineering La Trobe University

会议类型: 国际会议

会议名称: The 2010 International Conference on Intelligent Systems and Knowledge Engineering(第五届智能系统与知识工程国际会议)

会议地点: 杭州

会议语种:英文

页码: 331-337

在线出版日期: 2010-11-15（万方平台首次上网日期，不代表论文的发表时间）