An Efficient Model for Sentiment Analysis of Electronic Product Reviews in Vietnamese

被引：3

作者：

Suong N Hoang ^{[1
,2
]}

Linh V Nguyen ^{[1
]}

Tai Huynh ^{[1
,2
]}

Vuong T Pham ^{[1
,3
]}

机构：

[1] Kyanon Digital, Ho Chi Minh City, Vietnam

[2] Advosights, Ho Chi Minh City, Vietnam

[3] Saigon Univ, Ho Chi Minh City, Vietnam

来源：

FUTURE DATA AND SECURITY ENGINEERING (FDSE 2019) | 2019年 / 11814卷

关键词：

Vietnamese; Sentiment analysis; Electronics product review;

D O I：

10.1007/978-3-030-35653-8_10

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 the past few years, the growth of e-commerce and digital marketing in Vietnam has generated a huge volume of opinionated data. Analyzing those data would provide enterprises with insight for better business decisions. In this work, as part of the Advosights project, we study sentiment analysis of product reviews in Vietnamese. The final solution is based on Self-attention neural networks, a flexible architecture for text classification task with about 90.16% of accuracy in 0.0124 second, a very fast inference time.

引用

页码：132 / 142

页数：11

共 50 条

[31] Feature-based sentiment analysis approach for product reviews
Liu, L. (xxgccnu@126.com), 1600, Academy Publisher (09): : 274 - 279
[32] Product Opinion Mining Using Sentiment Analysis on Smartphone Reviews
Chawla, Shilpi
Dubey, Gaurav
Rana, Ajay
2017 6TH INTERNATIONAL CONFERENCE ON RELIABILITY, INFOCOM TECHNOLOGIES AND OPTIMIZATION (TRENDS AND FUTURE DIRECTIONS) (ICRITO), 2017, : 377 - 383
[33] User specific product recommendation and rating system by performing sentiment analysis on product reviews
Kiran, Vamsee Krishna M.
Vinodhini, R. E.
Archanaa, R.
Vimalkumar, K.
2017 4TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING AND COMMUNICATION SYSTEMS (ICACCS), 2017,
[34] Explainable sentiment analysis for product reviews using causal graph embeddings
Yadavilli, V. R. P. S. Sastry
Seshadri, Karthick
SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES, 2022, 47 (04):
[35] Sentiment Analysis of Product Reviews in Russian using Convolutional Neural Networks
Smetanin, Sergey
Komarov, Mikhail
2019 IEEE 21ST CONFERENCE ON BUSINESS INFORMATICS (CBI), VOL 1, 2019, : 482 - 486
[36] Semantic Features for Optimizing Supervised Approach of Sentiment Analysis on Product Reviews
Rintyarna, Bagus Setya
Sarno, Riyanarto
Fatichah, Chastine
COMPUTERS, 2019, 8 (03)
[37] Explainable Sentence-Level Sentiment Analysis for Amazon Product Reviews
Li, Xuechun
Sun, Xueyao
Xu, Zewei
Zhou, Yifan
2021 5TH INTERNATIONAL CONFERENCE ON IMAGING, SIGNAL PROCESSING AND COMMUNICATIONS (ICISPC 2021), 2021, : 88 - 94
[38] Amazon Product Reviews: Sentiment Analysis Using Supervised Learning Algorithms
Hawlader, Mohibullah
Ghosh, Arjan
Raad, Zaoyad Khan
Chowdhury, Wali Ahad
Shehan, Md Sazzad Hossain
Bin Ashraf, Faisal
PROCEEDINGS OF INTERNATIONAL CONFERENCE ON ELECTRONICS, COMMUNICATIONS AND INFORMATION TECHNOLOGY 2021 (ICECIT 2021), 2021,
[39] Sentiment analysis from product reviews using SentiWordNet as lexical resource
Cernian, Alexandra
Sgarciu, Valentin
Martin, Bogdan
PROCEEDINGS OF THE 2015 7TH INTERNATIONAL CONFERENCE ON ELECTRONICS, COMPUTERS AND ARTIFICIAL INTELLIGENCE (ECAI), 2015, : WE15 - WE18
[40] Online Reviews Sentiment Analysis and Product Feature Improvement with Deep Learning
Cao, Jihua
Li, Jie
Yin, Miao
Wang, Yunfeng
ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING, 2023, 22 (08)

← 1 2 3 4 5 →