Opinion mining of product reviews based on semantic role labeling

Online product reviews are becoming increasingly available. Generally, potential customers usually wade through a lot of online reviews in order to make an informed decision. We tackle the problem of semantic understanding for consumer reviews based on semantic role labeling, which implements shallow semantic analysis. In this paper, a sentiment mining and retrieval system was proposed, which mines useful knowledge from product reviews. Furthermore, the sentiment orientation and comparison between positive and negative evaluation are presented visually in the system. Experimental results on a real-world data set have shown the system is both feasible and effective.