A Linguistic Intuitionistic Cloud Decision Support Model with Sentiment Analysis for Product Selection in E-commerce

被引：65
作者：
Liang, Ruxia [1 ]
Wang, Jian-qiang [1 ]
机构：
[1] Cent South Univ, Sch Business, Changsha 410083, Peoples R China
来源：
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS | 2019年 / 21卷 / 03期
关键词：
Decision support model; Online reviews; Sentiment analysis; Linguistic intuitionistic fuzzy sets; ONLINE REVIEWS; INFORMATION; OPERATORS; RESPONSES; RATINGS; NUMBERS;
D O I：
10.1007/s40815-019-00606-0
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Online product reviews significantly impact the online purchase decisions of consumers. However, extant decision support models have neglected the randomness and fuzziness of online reviews and the interrelationships among product features. This study presents an integrated decision support model that can help customers discover desirable products online. This proposed model encompasses three modules: information acquisition, information transformation, and integration model. We use the information acquisition module to gather linguistic intuitionistic fuzzy information in each review through sentiment analysis. We also apply the information transformation module to convert the linguistic intuitionistic fuzzy information into linguistic intuitionistic normal clouds (LINCs). The integration module is employed to obtain the overall LINCs for each product. A ranked list of alternative products is determined. A case study on Taobao.com is then provided to illustrate the effectiveness and feasibility of the proposal, along with sensitivity and comparison analyses, to verify its stability and superiority. Finally, conclusions and future research directions are suggested.
引用
收藏
页码：963 / 977
页数：15
相关论文
共 50 条
[41]   An FMCDM approach to purchasing decision-making based on cloud model and prospect theory in e-commerce [J].
Zhang, Hong-yu ;
Zhou, Rui ;
Wang, Jian-qiang ;
Chen, Xiao-hong .
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, 2016, 9 (04) :676-688
[42]   Sentiment Mining in E-Commerce: The Transformer-based Deep Learning Model [J].
Alsaedi, Tahani ;
Nawaz, Asif ;
Alahmadi, Abdulrahman ;
Rana, Muhammad Rizwan Rashid ;
Raza, Ammar .
INTERNATIONAL JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING SYSTEMS, 2024, 15 (08) :641-650
[43]   F_ MixBERT: Sentiment Analysis Model using Focal Loss for Imbalanced E-commerce Reviews [J].
Pang, Fengqian ;
Chen, Xi ;
Li, Letong ;
Xu, Xin ;
Xing, Zhiqiang .
KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, 2024, 18 (02) :263-283
[44]   A Novel AB-CNN Model for Multi-Classification Sentiment Analysis of e-Commerce Comments [J].
Li, Hongchan ;
Lu, Yantong ;
Zhu, Haodong ;
Ma, Yu .
ELECTRONICS, 2023, 12 (08)
[45]   Sentiment analysis method for e-commerce review on weak-label data and deep learning model [J].
Zhou Z. ;
Chen J. ;
Wu J. .
International Journal of Wireless and Mobile Computing, 2024, 26 (01) :9-18
[46]   A REVIEW ON THE CONCEPT OF SENTIMENT ANALYSIS AND ITS ROLE IN MARKETING STRATEGIES FOR E-COMMERCE [J].
Reddy, Bhanu Sree ;
Jaidev, Uma Pricilda .
IIOAB JOURNAL, 2016, 7 (05) :216-224
[47]   Sentiment Analysis in E-Commerce Platforms: A Review of Current Techniques and Future Directions [J].
Huang, Huang ;
Zavareh, Adeleh Asemi ;
Mustafa, Mumtaz Begum .
IEEE ACCESS, 2023, 11 :90367-90382
[48]   E-Commerce Brand Ranking Algorithm Based on User Evaluation and Sentiment Analysis [J].
Chen, Nie .
FRONTIERS IN PSYCHOLOGY, 2022, 13
[49]   Sentiment Analysis of Roman Urdu on E-Commerce Reviews Using Machine Learning [J].
Chandio, Bilal ;
Shaikh, Asadullah ;
Bakhtyar, Maheen ;
Alrizq, Mesfer ;
Baber, Junaid ;
Sulaiman, Adel ;
Rajab, Adel ;
Noor, Waheed .
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES, 2022, 131 (03) :1263-1287
[50]   Feature selection for semi-supervised sentiment analysis of e-commerce reviews using CNN and neutrosophic fuzzy parameters [J].
Jena, Alok Kumar ;
Gopal, K. Murali ;
Tripathy, Abinash ;
Tripathy, Siba Prasada .
KNOWLEDGE AND INFORMATION SYSTEMS, 2025,
12345