计算机工程
計算機工程
계산궤공정
COMPUTER ENGINEERING
2015年
4期
171-175
,共5页
图模型%情感词%条件随机场%支持向量机%网页排序算法%倾向性分析
圖模型%情感詞%條件隨機場%支持嚮量機%網頁排序算法%傾嚮性分析
도모형%정감사%조건수궤장%지지향량궤%망혈배서산법%경향성분석
graph model%emotional words%condition random field%Support Vector Machine ( SVM )%PageRank algorithm%orientation analysis
为研究情感词对情感倾向分析的作用，提高微博情感分析性能，提出一种情感词图模型的方法，利用PageRank算法计算出情感词的褒贬权值，将其作为条件随机场模型的特征，预测具体语言环境下的情感词倾向。结合具体语境下的情感词倾向，利用支持向量机模型进行微博语料的主客观分类和情感倾向分类。实验结果表明，图模型构造的情感词典增加了具体语境下情感词倾向预测的准确性，具体语境下的情感词倾向预测对主客观分类和情感倾向分类有明显的改善。
為研究情感詞對情感傾嚮分析的作用，提高微博情感分析性能，提齣一種情感詞圖模型的方法，利用PageRank算法計算齣情感詞的褒貶權值，將其作為條件隨機場模型的特徵，預測具體語言環境下的情感詞傾嚮。結閤具體語境下的情感詞傾嚮，利用支持嚮量機模型進行微博語料的主客觀分類和情感傾嚮分類。實驗結果錶明，圖模型構造的情感詞典增加瞭具體語境下情感詞傾嚮預測的準確性，具體語境下的情感詞傾嚮預測對主客觀分類和情感傾嚮分類有明顯的改善。
위연구정감사대정감경향분석적작용，제고미박정감분석성능，제출일충정감사도모형적방법，이용PageRank산법계산출정감사적포폄권치，장기작위조건수궤장모형적특정，예측구체어언배경하적정감사경향。결합구체어경하적정감사경향，이용지지향량궤모형진행미박어료적주객관분류화정감경향분류。실험결과표명，도모형구조적정감사전증가료구체어경하정감사경향예측적준학성，구체어경하적정감사경향예측대주객관분류화정감경향분류유명현적개선。
For the further research of the function of emotional words on emotional analysis and the improvement of microblog emotional analysis method,this paper proposes a research approach to construct emotional words graph model using relations between emotional words. The emotional value of appraisal calculated by PageRank algorithm and trained as the feature of conditional random field model so as to forecast the tendency of emotional words in specific situations, through which subjectivity classification and emotional tendency analysis of microblog can be made when integrated with Support Vector Machine(SVM) model. Experimental results show that emotional lexicon constructed by graph model enhances accuracy of the prediction of emotional word in specific situations which is also helpful for subjectivity classification and emotional tendency analysis of mircroblog.
