基于关联特征词表的中文比较句识别

Chinese comparative sentences recognition based on associated feature vocabulary

中文比较句研究多集中于语言学领域,然而利用机器学习的方法识别比较句的研究才刚刚起步。根据关联规则挖掘算法的基本原理提出一种基于关联特征词表的比较句识别方法,该方法将词和词性作为一个基本元素,定义特征词表中核心词和依存词之间的关联方式,利用支持向量机(SVM)分类器进行比较句的识别。实验结果表明,该方法能够有效地识别出中文比较句,在准确率、召回率和F值上均取得不错的效果。

Chinese comparative sentences are more focused in the field of linguistics. Using machine learning methods to identify comparative sentences, however, has only just started. According to the basic principle of the association rules mining algorithm, a method of comparative sentences based on the associated feature vocabulary was proposed. This method regarded word and part of speech as basic elements, defined the connecting way between the table definition core words and imerdependent relationship words, and used the Support Vector Machine （SVM） classifier for the identification of comparative sentences. The experimental results show that this method can effectively identify Chinese comparative sentences, and achieves good results in precision, recall and F-measure.