Extracting Aspects in Product Reviews of Vietnamese e-Commerce Websites

被引：1

作者：

Ngoc Truong ^{[1
]}

Truong-Thang Nguyen ^{[1
]}

Thai-Le Luong ^{[2
]}

机构：

[1] Vietnam Acad Sci & Technol, Inst Informat Technol, Hanoi, Vietnam

[2] Univ Transport & Commun, Hanoi, Vietnam

来源：

INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY | 2020年 / 20卷 / 11期

关键词：

Aspect extract; product review; sentiment analysis; customer profile;

D O I：

10.22937/IJCSNS.2020.20.11.11

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In earlier times, there are many studies to extract from customers' product reviews on social networks, e-commerce websites, etc. However, in the Vietnamese market with different characteristics of culture and language have only a few studies published. Thus, in this paper, we present a deep convolutional neural network (D-CNN) architecture using features and linguistic patterns of the Vietnamese language for the aspect extraction task. The archived results are acceptable with F1 scores for three domain book, female fashion, and mobile accessories are 76.92%, 71.74%, and 74.54%, respectively.

引用

页码：89 / 95

页数：7

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