摘要
情感分析方法能够在海量的汽车评论信息中挖掘出有价值的信息,在汽车产品设计、品牌营销等方面具有较大的应用价值.针对汽车评论分析的细粒度分析要求,本文提出了基于实体的细粒度情感分析方法.首先,对汽车评论数据进行文本细粒度处理,然后采用Linear-chain CRF模型对评论数据进行情感实体识别和情感倾向分类;再对Linearchain CRF模型进行改进,提出了一种构造双层结构的CRF模型的方法,解决2个任务间的关联问题.实验结果表明,双层结构CRF模型的情感分析效果优于Linear-chain CRF模型,能够满足汽车评论在情感实体识别与情感倾向分类的需求.
Sentiment analysis method can mine valuable information from a mass of automotive reviews,which has great application value in automotive product design and brand marketing.For the requirements of fine-grained analysis,a fine-grained sentiment analysis algorithm is put forward based on the entity.Firstly,the automotive reviews are preprocessed,then the model of Linear-chain CRF is used to do sentiment entity recognition and sentiment classification.Secondly,in order to relate the entity recognition with sentiment classification,the model of Linear-chain CRF is improved,and a method of two-level CRF proposed.Experimental results show that twolevel CRF is better than Linear-chain CRF in sentiment analysis,which can meet the demand of fine-grained sentiment analysis of automotive reviews.
作者
陈炳丰
郝志峰
蔡瑞初
温雯
王丽娟
黄浩
蔡晓凤
Chen Bing-feng;Hao Zhi-feng;Cai Rui-chu;Wen Wen;Wang Li-juan;Huang Hao;Cai Xiao-feng(School of Computers, Guangdong University of Technology, Guangzhou 510006, China;School of Mathematics and Big Data, Foshan University, Foshan 528000, China)
出处
《广东工业大学学报》
CAS
2017年第3期8-14,共7页
Journal of Guangdong University of Technology
基金
国家自然科学基金资助项目(U1501254
61472089
61572143)
广东省自然科学基金资助项目(2014A030308008)
广东省自然科学杰出青年基金资助项目(2014A030306004)
广东省科技计划项目(2015B010108006)
广东省教育厅项目(2015KQNCX027)
关键词
汽车评论
情感分析
情感词典
细粒度
条件随机场
automotive reviews
sentiment analysis
sentiment lexicon
fine-grained
conditional random field
