A Novel Approach of Extracting Opinion Targets and Opinion Words from Online Review

被引：0
|
作者：
Tang, Mingshuang [1 ]
Cheng, Hongrong [1 ]
Guo, Yanwei [1 ]
Luo, Jiaqing [1 ]
Zhou, Shijie [1 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Comp Sci & Engn, Chengdu 611731, Peoples R China
来源：
PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON EDUCATION, SPORTS, ARTS AND MANAGEMENT ENGINEERING | 2016年 / 54卷
关键词：
opinion mining; sentiment analysis; opinion target; opinion word;
D O I：
暂无
中图分类号：
G40 [教育学];
学科分类号：
040101 ; 120403 ;
摘要：
In opinion mining, the precision of extracting opinion words and opinion targets from online review dataset can severely influence the precision of opinion mining systems. In this paper, we propose a graph-based filtering approach to extract effective opinion targets and opinion words from the candidate words, which can be mined by word-based translation model in a monolingual scenario. Experimental results on four real Chinese review datasets show that our approach is promising performance.
引用
收藏
页码：118 / 121
页数：4
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