计算机应用研究2017，Vol.34Issue(4)：1000-1003,4.DOI:10.3969/j.issn.1001-3695.2017.04.009
基于复杂网络的情感分类特征选择
Emotional classification feature selection based on complex network
摘要
Abstract
Firstly,this paper created the sentiment word dictionary of professional field based on point mutual information theory,and used public domain dictionary emotion as seed semantic lexicon,and used adjective words in review crops which was not contained the public domain dictionary emotion as candidate emotional characteristics.The reason what the authors did was the applicability of public domain dictionary emotion used for professional field was not good.Secondly,it proposed a new algorithm for feature selection of emotional classification for online review based on complex network.It made better for semantic relativity between feature words,so that it got more emotive information.It created the relational complex network for candidate feature by complex network theory.Then it considered the part and overall important of nodes.It used degree centrality,betweeness centrality,closeness centrality to measure important of nodes for selecting emotional classification feature,the algorithm was named NTFS.At last,it used online reviews of iPhone for test data,used SVM,NNET,NB for classifier,and compared NTFS with GI and CHI.The result shows that NTFS is better than GI,CHI for emotional classification on classification performance.关键词
复杂网络/特征选择/情感分类/情感词典Key words
complex network/feature selection/emotional classification/semantic lexicon分类
信息技术与安全科学引用本文复制引用
张向阳,那日萨..基于复杂网络的情感分类特征选择[J].计算机应用研究,2017,34(4):1000-1003,4.基金项目
国家自然科学基金面上项目(61471083) （61471083）
国家教育部人文社科研究规划基金资助项目(14YJA630044) （14YJA630044）
