Classification of Vietnamese Reviews on E-Commerce Platforms
Phan Thi Ha1, Trinh Thi Van Anh2
1Dr. Phan Thi Ha, Lecturer, Faculty of Information Technology at Posts and Telecommunications Institute of Technology (PTIT), Ha Noi, Vietnam, and Computing Fundamental Department, FPT University, Hanoi, Viet Nam.
2Trinh Thi Van Anh, Lecturer, Faculty of Information Technology at Posts and Telecommunications Institute of Technology (PTIT) in Ha Noi, Vietnam, and Computing Fundamental Department, FPT University, Hanoi, Viet Nam.
Manuscript received on 01 August 2024 | Revised Manuscript received on 07 August 2024 | Manuscript Accepted on 15 September 2024 | Manuscript published on 30 September 2024 | PP: 7-11 | Volume-13 Issue-10, September 2024 | Retrieval Number: 100.1/ijitee.J996313100924 | DOI: 10.35940/ijitee.J9963.13100924
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The research team utilised machine learning models to classify Vietnamese product reviews on an e-commerce platform as either positive or negative. To categorise and evaluate the effectiveness of Support Vector Machine (SVM), Random Forest, and Logistic Regression machine learning models on different platforms, the authors have built their own training and test datasets, as well as a set of stopwords, to classify Vietnamese web reviews [9]. This can then be applied to building a web app that allows users to enter a link of any online product and categorise its user reviews, helping sellers evaluate their products and services, understand consumer behaviour, and make changes or improvements accordingly.
Keywords: Text Classification, SVM, Random Forest, Logistic Regression, CNN.
Scope of the Article: Computer Science and Applications