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

页码：118 / 121

页数：4

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