CAJ | 학술논문

针对中文消费评价的情感分类问题,构造基于词典语义概念和上下文语义相结合的情感分类方法,对情感进行分类。该方法首先构造提取不同领域基准词集的方法。然后利用一元语言模型,通过HowNet计算情感相似值,进行情感词提取。最后结合HowNet方法和Google相似距离方法构造一种情感分类算法,对句子进行情感倾向性分类,既考虑词语本身含义,又考虑词语在上下文中的含义。通过对书籍、电脑和酒店的评价进行实验,F值较高,同时与其他方法进行对比实验,体现文中算法的有效性。
침대중문소비평개적정감분류문제,구조기우사전어의개념화상하문어의상결합적정감분류방법,대정감진행분류。해방법수선구조제취불동영역기준사집적방법。연후이용일원어언모형,통과HowNet계산정감상사치,진행정감사제취。최후결합HowNet방법화Google상사거리방법구조일충정감분류산법,대구자진행정감경향성분류,기고필사어본신함의,우고필사어재상하문중적함의。통과대서적、전뇌화주점적평개진행실험,F치교고,동시여기타방법진행대비실험,체현문중산법적유효성。
Aiming at the sentiment classification for Chinese consumption comments, a sentiment classification method combining dictionary semantic concept and context semanteme is proposed. Firstly, a method of extracting benchmark words set of different domains is put forword. Then, the sentiment words are extracted through the similarity of HowNet based on the unigram model. Finally, HowNet and Google similarity distance ( HGSD ) combining the HowNet similarity and the Google similarity distance is presented to classify the sentences, which reflects the original meaning of the word and the meaning in the context. Experiments of consumption comments on books, computers and hotels show the higher F-measure of the proposed method, and meanwhile the contrast experiment shows the effectiveness of the proposed algorithm.