Extraction of Product Defects and Opinions from Customer Reviews by Using Text Clustering and Sentiment Analysis

被引：2

作者：

Cataltas, Mustafa ^{[1
]}

Dogramaci, Sevcan ^{[1
]}

Yumusak, Semih ^{[2
]}

Oztoprak, Kasim ^{[1
]}

机构：

[1] Konya Food & Agr Univ, Comp Engn, Konya, Turkey

[2] KTO Karatay Univ, Comp Engn, Konya, Turkey

来源：

2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA) | 2020年

关键词：

natural language processing; feature extraction; opinion mining; text summarization;

D O I：

10.1109/BigData50022.2020.9377851

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The development of e-commerce has created new shopping trends of customers. In online shopping environments, product reviews play a critical role in the choice of customers. Online reviews are additionally valuable for the manufacturers and the vendors by providing easily accessible feedback to them. In this study, a text analysis method is proposed to find the defective features of the products by detecting features with negative opinion tendency in the clustered customer reviews. The output of the proposed model, the extracted defects, may provide a strong source of guidance both for consumers in purchase decisions and for producers in product improvement.

引用

页码：4529 / 4534

页数：6

共 50 条

[31] A Study on Sentiment Analysis of Product Reviews
Parihar, Anil Singh
Bhagyanidhi
IEEE INTERNATIONAL CONFERENCE ON SOFT-COMPUTING AND NETWORK SECURITY (ICSNS 2018), 2018, : 5 - 9
[32] Sentiment Analysis of Product Reviews: A Review
Shivaprasad, T. K.
Shetty, Jyothi
PROCEEDINGS OF THE 2017 INTERNATIONAL CONFERENCE ON INVENTIVE COMMUNICATION AND COMPUTATIONAL TECHNOLOGIES (ICICCT), 2017, : 298 - 303
[33] A Distant Supervision Method for Product Aspect Extraction from Customer Reviews
Bross, Juergen
2013 IEEE SEVENTH INTERNATIONAL CONFERENCE ON SEMANTIC COMPUTING (ICSC 2013), 2013, : 339 - 346
[34] Sentiment Analysis Based Product Rating Using Textual Reviews
Sindhu, C.
Vyas, Dyawanapally Veda
Pradyoth, Kommareddy
2017 INTERNATIONAL CONFERENCE OF ELECTRONICS, COMMUNICATION AND AEROSPACE TECHNOLOGY (ICECA), VOL 2, 2017, : 727 - 731
[35] 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
[36] Gather customer concerns from online product reviews - A text summarization approach
Zhan, Jiaming
Loh, Han Tong
Liu, Ying
EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (02) : 2107 - 2115
[37] Latent Customer Needs Elicitation by Use Case Analogical Reasoning From Sentiment Analysis of Online Product Reviews
Zhou, Feng
Jiao, Roger Jianxin
Linsey, Julie S.
JOURNAL OF MECHANICAL DESIGN, 2015, 137 (07)
[38] A short text sentiment-topic model for product reviews
Xiong, Shufeng
Wang, Kuiyi
Ji, Donghong
Wang, Bingkun
NEUROCOMPUTING, 2018, 297 : 94 - 102
[39] Sentiment Analysis for Reviews of Restaurants in Myanmar Text
Aye, Yu Mon
Aung, Sint Sint
2017 18TH IEEE/ACIS INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING, ARTIFICIAL INTELLIGENCE, NETWORKING AND PARALLEL/DISTRIBUTED COMPUTING (SNDP 2017), 2017, : 321 - 326
[40] Technical Aspect Extraction from Customer Reviews Based on Seeded Word Clustering
Davril, Jean-Marc
Leclercq, Tony
Cordy, Maxime
Heymans, Patrick
NATURAL LANGUAGE PROCESSING AND INFORMATION SYSTEMS, NLDB 2017, 2017, 10260 : 97 - 109

← 1 2 3 4 5 →