自动化学报2017，Vol.43Issue(3)：462-471,10.DOI:10.16383/j.aas.2017.c160060
基于多层关系图模型的中文评价对象与评价词抽取方法
A Multi-layer Relation Graph Model for Extracting Opinion Targets and Opinion Words
摘要
Abstract
Mining opinion targets and opinion words is a fundamental task for the Chinese online media to mine opinion and analyze sentiment. The key to enhancing the effectiveness of opinion target and opinion word is to integrate syntactic relations and co-occurrence relations between opinion target and opinion word into the mining model. A novel approach based on a multi-layer relation graph model is proposed to extract opinion targets and opinion words from Chinese social media. First, the word alignment model is employed to extract the candidates of opinion target and opinion word candidates. Second, a multi-layer relation graph is constructed by the syntactic inter-relations between opinion target and opinion word, the co-occurrence intra-relations among opinion targets, and the co-occurrence intra-relations among opinion words. Third, a random-walk algorithm is adopted to calculate the confidence of each opinion target candidate and opinion word candidate. Finally, opinion targets and opinion words are extracted according to their confidence values. Experimental results show that the presented method can not only achieve significant improvement over previous methods, but also have good robustness.关键词
倾向性分析/观点挖掘/依存句法分析/随机游走Key words
Sentiment analysis/opinion mining/dependency syntactic parsing/random walk引用本文复制引用
廖祥文,陈兴俊,魏晶晶,陈国龙,程学旗..基于多层关系图模型的中文评价对象与评价词抽取方法[J].自动化学报,2017,43(3):462-471,10.基金项目
国家自然科学基金青年项目(61300105),中国科学院网络数据科学与技术重点实验室开放基金课题(CASNDST20140X)资助Supported by National Natural Science Foundation of China(61300105),Key Laboratory of Network Data Science & Tech-nology,Chinese Science and Technology Foundation(CAS-NDST20140X) （61300105）
