摘要
针对情感分析工作中需要繁琐的人工标注问题,提出一种基于评价单元五元组的情感分析方法。该方法只需合适的情感词典,不需要大量人工标注即可对其进行情感倾向分析。通过联合无监督和有监督学习方法构建评价词表和评价对象词表,在此基础上采用以情感词为链的线性条件随机场模型构建评价单元。最后根据语意搭配关系将评价对象分为4类,情感词分为5类,结合句型、否定词、程度词对情感分析的影响,提出计算文本情感倾向的方法。对比实验表明,本文方法在明显减少人工工作的前提下,取得了较高的F值,并且具有一定的跨领域性。
Aiming at the problem of manual annotation in the text sentiment analysis, a new method based on five tuple of ap- praisal expression is proposed. This method just needs appropriate sentiment dictionary. The sentiment tendencies of comments are analyzed without lots of markup work. Through the combination of unsupervised and supervised learning methods to construct the evaluation thesaurus and evaluation object list; the extraction of appraisal expression is based on these lists, using linear chain conditional random fields model, which is in the chain of sentiment words. Finally, evaluation objects are divided into four cate- gories and emotional words are divided into five types according to the relationship between semantic collocation, combined with the influence of sentence pattern, negative word and degree word on the sentiment analysis, a method of calculating the sentiment tendency of the text is put forward. Compared with other methods, this method based on the appraisal expression has obtained bet- ter F value, and it has a certain cross domain.
出处
《计算机与现代化》
2017年第7期10-15,52,共7页
Computer and Modernization
关键词
情感分类
信息抽取
意见挖掘
情感分析
sentiment classification
information extract
opinion mining
sentiment analysis
