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摘要:
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.
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篇名 Chinese Explanatory Segment Recognition as Sequence Labeling
来源期刊 国际计算机前沿大会会议论文集 学科 社会科学
关键词 OPINION mining explanatory SEGMENT RECOGNITION product REVIEWS
年,卷(期) 2015,(1) 所属期刊栏目
研究方向 页码范围 46-48
页数 3页 分类号 C5
字数 语种
DOI
五维指标
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研究主题发展历程
节点文献
OPINION
mining
explanatory
SEGMENT
RECOGNITION
product
REVIEWS
研究起点
研究来源
研究分支
研究去脉
引文网络交叉学科
相关学者/机构
期刊影响力
国际计算机前沿大会会议论文集
半年刊
北京市海淀区西三旗昌临801号
出版文献量(篇)
616
总下载数(次)
6
总被引数(次)
0
论文1v1指导