基于依存关系分析的网络评论极性分类研究

Research of polarity classification of Web review based on dependency analysis

介绍一种利用句法依存关系对网络评论的极性进行自动分类的方法。通过从评论中提取出依存关系和词性,构成依存关系词性对,并利用自定义的极性词典进行分类,有效地减少计算的复杂度和提高分类的精度。实验表明,该方法相比其他方法取得了较好的分类效果,是一种可行且有效的对评论极性分类的方法。

A polarity classification approach of web review based on dependency analysis is proposed.Dependencies and part-ofspeeches are extracted from web review to construct dependency and part-of-speech pairs,and then classification by polarity dictionary is accomplished.The approach can effectively reduce the complexity of calculation and improve the accuracy of classification,by using dependency and part-of-speech pair and custom polar dictionary.This experiment results show that the approach will obtain higher performance compared with other classification approaches.It is a feasible and valid polarity classification approach of web review.