计算机工程Issue(10)：167-171,5.DOI:10.3969/j.issn.1000-3428.2013.10.035
基于特征变换的跨领域产品评论倾向性分析
Opinion Analysis of Cross-domain Product Review Based on Feature Transformation
摘要
Abstract
Traditional sentiment analysis methods aim at same domain documents, the performance becomes worse for different domain documents. To solve this problem, this paper presents an opinion analysis method of cross-domain product reviews based on feature transformation. This proposed method builds the relevance of domain dependent words between source domain and target domain via domain independent words so that it can transfer acknowledge from the source domain to the target domain. It solves the classifier performance decreasing problem due to different data distributions. The product reviews are used as a corpus in the experiment. The average accuracies are 76.61% and 76.81% by using the methods of Support Vector Machine(SVM) and logistic regression respectively in all corpora. The results are higher than Baseline algorithm.关键词
特征变换/倾向性分析/产品评论/源领域/目标领域/领域独立词/领域依赖词Key words
feature transformation/opinion analysis/product review/source domain/target domain/domain independent word/domain dependent word分类
信息技术与安全科学引用本文复制引用
孟佳娜,段晓东,杨亮..基于特征变换的跨领域产品评论倾向性分析[J].计算机工程,2013,(10):167-171,5.基金项目
国家自然科学基金资助项目(61202254)；中国博士后科学基金资助项目(2013M530918)；中央高校自主科研基金资助项目(DC120101081, DC120101084)；辽宁省教育厅科学研究基金资助一般项目(L2012478) （61202254）
