CAJ | 학술논문

产品评论的情感倾向性分析是一个很有研究价值的领域，可以帮助客户、商家进行决策。针对产品评论中的属性词和情感词在文本中的各种关系，制定了8组特征选择规则，利用SVM算法训练模型来判断属性词和情感词的搭配识别，进而依据情感词及否定词等分析属性特征的情感倾向。实验结果表明：提出的基于SVM的搭配识别方法，在识别属性特征与情感词的搭配方面具有不错的分类效果。
산품평론적정감경향성분석시일개흔유연구개치적영역，가이방조객호、상가진행결책。침대산품평론중적속성사화정감사재문본중적각충관계，제정료8조특정선택규칙，이용SVM산법훈련모형래판단속성사화정감사적탑배식별，진이의거정감사급부정사등분석속성특정적정감경향。실험결과표명：제출적기우SVM적탑배식별방법，재식별속성특정여정감사적탑배방면구유불착적분류효과。
Emotion analysis of product reviews is a valuable research field, it can help customers and merchants make decisions. Based on various relations of attribute words and emotion words in product review texts, develops eight sets of feature selection rules, and applies SVM algorithm training model to judge the identification of attribute words and emotions words, then analyzes the emotion tendencies of attribute characteristics based on emotion words and negative words. The experimental results show: the proposed SVM-based recognition method achieves good classification effect in the identi- fication of attributes and emotion words.