评价对象抽取及其倾向性分析

Comment Target Extraction and Sentiment Classification

情感分析近年来已经成为自然语言处理领域的热点问题,该文对情感分析中的两项关键技术——评价对象抽取和倾向性判断进行了深入研究。在评价对象抽取阶段,首先使用句法分析结果获取候选评价对象,继而结合基于网络挖掘的PMI算法和名词剪枝算法对候选评价对象进行筛选。在倾向性判断阶段,通过分析情感句句型,归纳相应的分析规则,使用无指导的方法完成评价对象在情感句中的倾向性判断。该系统参加了COAE2008任务三的评测,取得了较好成绩。

The research on sentiment analysis is a hot issue in natural language processing. This paper makes an intensive study of the two stages of sentiment analysis： the comment target extraction and the corresponding sentiment classification. For the first task, we use the syntactic analysis to obtain the candidats, and then combine PMI based on web mining and NN filtering algorithm to decide the targets. For the second task, we design certain heuristic rules by analyzing subjective sentences, and then apply these rules to predict the orientation of opinion in the sen- tences. This method performs well in Task Three of the COAE2008 i.