计算机应用研究2016，Vol.33Issue(3)：682-685,4.DOI:10.3969/j.issn.1001-3695.2016.03.010
基于语义空间的藏文微博情感分析方法
Emotional classification method of Tibetan micro-blog based on semantic space
摘要
Abstract
Tibetan micro-blog has unique grammatical features,traditional classification method can achieve good results but for Tibetan classification efficiency is not better.This paper presented an emotional classification method of Tibetan micro-blog that based on the semantic space with Tibetan syntactic structure.Firstly,the method generated the syntactic structure using the syntax tree.Then it combined syntactic structure and semantic feature vector to construct the semantic feature space.In the feature space,it formed semantic cluster centroid by K-means clustering method.Finally,it calculated the emotional values of micro-blog by TF-IDF based on the clusters.Experimental results show that this method can more accurately classify on Ti-betan micro-blog emotion,compared with SVM+TFI-DF and naive Bayes +maximum entropy.关键词
藏语微博/情感分类/语义空间/文本聚类/语义簇Key words
Tibetan micro-blog/emotional classification/semantic space/text clustering/semantic clusters分类
信息技术与安全科学引用本文复制引用
袁斌,江涛,于洪志..基于语义空间的藏文微博情感分析方法[J].计算机应用研究,2016,33(3):682-685,4.基金项目
国家自然科学基金资助项目（61262054）；甘肃省科技重大专项资助项目（1203FKDA033）；西北民族大学中央专项资金资助研究生项目（Yxm2014001）；国家科技支撑计划资助项目 （）
