Recognizing Sentiment Polarity in Chinese Reviews Based on Topic Sentiment Sentences

摘要：

We present an approach to recognizing sentiment polarity in Chinese reviews based on topic sentiment sentences. Considering the features of Chinese reviews, we firstly identify the topic of a review using an n-gram matching approach. To extract candidate topic sentiment sentences, we compute the semantic similarity between a given sentence and the ascertained topic and meanwhile determine whether the sentence is subjective. A certain number of these sentences are then selected as representatives according to their semantic similarity value with relation to the topic. The average value of the representative topic sentiment sentences is calculated and taken as the sentiment polarity of a review. Experiment results show that the proposed method is feasible and can achieve relatively high precision.

关键词： Sentiment polarity topic sentiment sentence Chinese reviews semantic similarity sentiment

作者: Jiang YANG Min HOU Ning WANG

作者单位: School of Literature,Communication University of China　Beijing, China Broadcast Media Language　Branch, Communication　University of China　Beijing, China School of Literature, Communication University of China Beijing, China

会议类型: 国际会议

会议名称: The 6th International Conference on Natural Language Processing and Knowledge Engineering(第六届IEEE自然语言处理与知识工程国际会议 NLP-KE 2010)

会议地点: 北京

会议语种:英文

页码: 1-6

在线出版日期: 2010-08-21（万方平台首次上网日期，不代表论文的发表时间）