Chinese explanatory segment recognition as sequence labeling

Abstract

How to mine the underlying reasons for opinions is a key issue on opinion mining. In this paper, we propose a CRF-based labeling approach to explanatory segment recognition in Chinese product reviews. To this end, we first reformulate explanatory segments recognition as a labeling task on a sequence of words, and then explore various features from three linguistic levels, namely character, word and semantic under the framework of conditional random fields. Experimental results over product reviews from mobilephone and car domains show that the proposed approach significantly outperforms existing state-of-the-art methods for explanatory segment extraction.