摘要
针对当前句法关系研究存在过多考虑主谓关系、情感词识别能力有限、忽视隐式特征提取等方面的不足,提出一种基于句法规则与情感词的隐式特征提取方法。借助中文情感词典资源,基于外部语料与实验语料训练的词向量分别构建混合情感词典和产品特征词典,通过词典和定义的句法规则提取显式特征及情感词,根据其共现关系提取隐式特征。在相机评论语料集上进行实验并与现有方法进行对比,实验结果表明,该方法能有效提取显式及隐式特征,在获取全面特征信息上具有较好的性能。
In view of the shortcomings of the current syntactic relations research in considering mostly subject-predicate relations,limited recognition ability of sentiment words and neglecting implicit feature extraction,an implicit feature extraction method based on syntactic rules and sentiment words was proposed.By means of Chinese sentiment dictionary resources and word vectors trained based on external and experimental corpus,a hybrid sentiment dictionary and a product feature dictionary were constructed respectively.The dictionary and the defined syntactic rules were used to extract explicit features and sentiment words,and implicit features were extracted according to their co-occurrence relations.Experiments were conducted on camera review corpus and compared with existing methods.Results show that the proposed method can effectively extract explicit and implicit features,and has better performance in obtaining comprehensive feature information.
作者
陈可嘉
柯永诚
林鸿熙
CHEN Ke-jia;KE Yong-cheng;LIN Hong-xi(School of Economics and Management,Fuzhou University,Fuzhou 350108,China;School of Business,Putian University,Putian 351100,China)
出处
《计算机工程与设计》
北大核心
2024年第3期740-747,共8页
Computer Engineering and Design
基金
国家自然科学基金项目(71701019)。
关键词
隐式特征
显式特征
句法规则
情感词
词向量
共现分析
产品评论
implicit feature
explicit feature
syntactic rule
sentiment word
word vector
co-occurrence analysis
product review
