张绍武

个人信息Personal Information

教授

硕士生导师

性别:男

毕业院校:大连理工大学

学位:博士

所在单位:计算机科学与技术学院

学科:计算机应用技术

办公地点:大黑楼B807

电子邮箱:zhangsw@dlut.edu.cn

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A Cross-Domain Sentiment Classification Method Based on Extraction of Key Sentiment Sentence

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论文类型:会议论文

发表时间:2015-10-09

收录刊物:EI、CPCI-S、Scopus

卷号:9362

页面范围:90-101

关键字:Cross-domain; Key sentiment sentence; Multi-view ensemble

摘要:Cross-domain sentiment analysis focuses on these problems where the source domain and the target domain are from different domains. However, traditional sentiment classification approaches usually perform poorly to address cross-domain problems. So, this paper proposed a cross-domain sentiment classification method based on extraction of key sentiment sentence. Firstly, based on the observation that not every part of the document is equally informative for inferring the sentiment orientation of the whole document, the concept of key sentiment sentence was defined. Secondly, taking advantage of three properties: sentiment purity, keyword property and position property, we construct heuristic rules, and combine with machine learning to extract key sentiment sentence. Then, data is divided into key and detail views. Integrating two views effectively can improve performance. Finally, experimental results show the superiority of our proposed method.