Extracting Product Features from Chinese Customer Reviews

被引：1

作者：

Zheng, Yu ^{[1
]}

Ye, Liang ^{[1
]}

Wu, Geng-feng ^{[1
]}

Li, Xin ^{[2
]}

机构：

[1] Shanghai Univ, Sch Engn & Comp Sci, Shanghai 200072, Peoples R China

[2] Shanghai Univ, Sch Electromech Engn & Automat, Shanghai 200072, Peoples R China

来源：

2008 3RD INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEM AND KNOWLEDGE ENGINEERING, VOLS 1 AND 2 | 2008年

关键词：

opinion mining; product feature extraction; customer review;

D O I：

10.1109/ISKE.2008.4730942

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

E-commerce, or business done on the Internet has become more and more popular. Meanwhile, the number of customer reviews for products on the internet grows rapidly. For a popular product, the number of reviews can be in hundreds. As a result, the problem of "opinion mining" has seen increasing attention over several years. In this paper, we proposed a statistical method to extract product features from Chinese customer reviews. The method is based on distribution of a candidate word in different domains and within the certain domain. It also takes into account the unbalance size of different product reviews. Experimental results show that it achieves better performance than other methods.

引用

页码：285 / +

页数：2

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