计算机技术与发展Issue(1)：74-77,4.DOI:10.3969/j.issn.1673-629X.2016.01.015
融合直推式学习和语义理解的词语倾向性识别
Identifying of Word Sentiment Orientation of Transductive Learning and Semantic Comprehension
摘要
Abstract
At present,the research on word sentiment orientation identification is mainly divided into machine learning and semantic com-prehension,but machine learning cannot handle general field words effectively,semantic comprehension also cannot get high scores at pre-cision and recall,therefore,a new fusion method between transductive learning and semantic comprehension for judging word polarity was put forward in this paper. Firstly the HowNet knowledge base system is improved,on the basis of four primitive,the fifth primitive—senti-mental primitive was proposed,which was integrated into HowNet manually,on the basis of this,then a new word sentimental similarity calculation method was proposed to compute word’s sentimental value. At last,combine this way with transductive learning for identif-ying word’s sentimental orientation. The performance of experiment shows that compared with SVM or traditional semantic comprehen-sion,it can get better results.关键词
词语倾向性识别/机器学习/语义理解/意见挖掘/情感义原/HowNetKey words
word sentiment orientation/machine learning/semantic comprehension/opinion mining/sentimental primitive/HowNet分类
信息技术与安全科学引用本文复制引用
闻彬,饶彬,赵君喆,焦翠珍,戴文华..融合直推式学习和语义理解的词语倾向性识别[J].计算机技术与发展,2016,(1):74-77,4.基金项目
国家自然科学基金面上项目(61373108) （61373108）
湖北省教育厅科研项目(Q20112809,B20082803) （Q20112809,B20082803）
湖北省教育厅人文社会科学研究项目(13g389) （13g389）
