Abstract:This paper describes sentiment classification research on Uyghur text using different keyword extraction methods to recognize common emotions like anger and happiness. The keywords expressing happiness and anger are extracted using the TextRank, sparse discriminant analysis (SDA) and sparse support vector machine (Sparse SVM) methods to train feature extraction and sentiment models. A sentiment text database was built by excerpting the anger and happiness sentiments from Uyghur movies and novels with several validation experiments based on those text databases. The tests show that the keyword extraction methods presented in this paper are effective for emotion classification from Uyghur sentences. The Sparse SVM method is robustness and has higher accuracy in recognition tests with a smaller number of keywords extracted.
谢晋. 基于词跨度的中文文本关键词提取及在文本分类中的应用[D]. 杭州:浙江工业大学, 2011. XIE Jin. Chinese Keyword Extraction Method Based on Word Span and Its Application in Text Classification[D]. Hangzhou:Zhejiang University of Technology, 2011. (in Chinese)
[2]
张彦博. 文本情感分类的研究[D]. 北京:北京交通大学, 2010. ZHANG Yanbo. Research of Text Sentiment Classification[D]. Beijing:Beijing Jiaotong University, 2010. (in Chinese)
[3]
李寿山. 情感文本分类方法研究[D]. 北京:中国科学院自动化研究所, 2008. LI Shoushan. Research on Sentiment Classification Method[D]. Beijing:Institute of Automation, Chinese Academy of Sciences, 2008. (in Chinese)
[4]
杨鼎, 阳爱民. 一种基于情感词典和朴素贝叶斯的中文文本情感分类方法[J]. 计算机应用研究, 2010, 27(10):3737-3743. YANG Ding, YANG Aimin. Classification approach of Chinese texts sentiment based on semantic lexicon and naive Bayesian[J]. Application Research of Computers, 2010, 27(10):3737-3743. (in Chinese)
[5]
潘文彬. 基于情感词词典的中文句子情感倾向性分析[D]. 北京:北京邮电大学, 2011. PAN Wenbin. The Sentimental Orientation Analysis of Sentence Based on Sentiment Dictionary[D]. Beijing:Beijing University of Posts and Telecommunications, 2011. (in Chinese)
[6]
张靖, 金浩. 汉语词语情感倾向自动判断研究[J]. 计算机工程, 2010, 36(23):194-196. ZHANG Jing, JIN Hao. Study on Chinese word sentiment polarity automatic estimation[J]. Computer Engineering, 2010, 36(23):194-196. (in Chinese)
[7]
黄俊, 田生伟, 禹龙, 等. 基于维吾尔语情感词的句子情感分析[J]. 计算机工程, 2012, 38(9):183-185. HUANG Jun, TIAN Shengwei, YU Long, et al. Sentence sentiment analysis based on Uyghur sentiment word[J]. Computer Engineering, 2012, 38(9):183-185. (in Chinese)
LI Juanzi, FAN Qi'na, ZHANG Kuo. Keyword extraction based on tf/idf for Chinese news document[J]. Wuhan University Journal of Natural Sciences, 2007, 5:917-921.
[10]
祖丽湖玛尔·马木提江. 维吾尔语区分性关键词提取应用软件开发及其性能分析[D]. 乌鲁木齐:新疆大学, 2013. Mamut Zulhumar. Research on Uyghur Discriminative Keyword Extraction Algorithm and Its Performance Analysis[D]. Urumqi:Xinjiang University, 2013. (in Chinese)
[11]
热依莱木·帕尔哈提, 孟祥涛, 艾斯卡尔·艾木都拉. 基于区分性关键词模型的维吾尔语文本情感分类[J]. 计算机工程, 2014, 40(10):132-136, 142. Rayila Parhat, MENG Xiangtao, Askar Hamdulla. Uyghur text sentiment classification based on discriminative keyword model[J]. Computer Engineering, 2014, 40(10):132-136, 142. (in Chinese)
[12]
Mihalcea R, Tarau P. TextRank:Bringing order into texts[C]//Empirical Methods in Natural Language Processing 2004. Barcelona, Spain, 2004:404-410.
[13]
陈小冬, 林焕祥. 稀疏判别分析[J]. 计算机应用, 2013, 32(4):1017-1021. CHEN Xiaodong, LIN Huanxiang. Sparse discriminant analysis[J]. Journal of Computer Applications, 2012, 32(4):1017-1021. (in Chinese)
[14]
Bi J, Bennett K, Embrechts M, et al. Dimensionality reduction via sparse support vector machines.[J]. Journal of Machine Learning Research, 2003, 3(3):1229-1243.
[15]
热依莱木·帕尔哈提. 文本关键词提取技术及其应用研究[D]. 乌鲁木齐:新疆大学, 2014. Rayila Parhat. The Effective Text Keyword Extraction Technologies and Their Applications[D]. Urumqi:Xinjiang University, 2014. (in Chinese)"