基于自动提取句法模板的情感分析

提出了一种自动化提取情感依存句法关系的分析方法。在待分析语句依存句法树的基础上,结合中文语法特点,定义了分枝、嫁接、剪枝和枝解四种基本操作,压缩依存树的特征空间的同时将语句转换成表征句法关系的子树集合,最后利用遗传算法求解最优情感子树集。针对第三届自然语言处理及中文计算会议(NLPCC 2014)评测数据的实验结果表明,该方法在语句是否表达情感的判别上具有优异效果。与基于词典的情感分析结合,可降低词典对客观句的高误判缺陷,进而明显改进基于词典的情感分析方法。

Emotion Analysis Based on Automatic Extraction of Syntactic Patterns

A new method for emotion analysis by automatic extraction of sentimental syntactic patterns is proposed. Based on the syntax dependency tree of the sentence to be analyzed, four basic operations are defined in this paper, i.e., branching, grafting, pruning and decomposing, according to Chinese grammatical characteristics. These operations can simultaneously compress the feature space of dependency tree and transform sentences into a set of subtrees representing syntactic relations. Finally, the genetic algorithm is used to obtain the optimal emotional subtrees. The experiments conducted on the evaluation data from NLPCC 2014 show that this method performs very well in judging whether a sentence expresses emotion or not. When combined with dictionary-based sentiment analysis, it can improve the performance of the dictionary-based sentiment analysis method by reducing its deficiency of high false positive rate on objective sentences.