Manh, Cuong Nguyen and Pham Minh, Hieu and Van, Hoang Do and Nguyen Quoc, Khanh and Nguyen, Khanh and Van, Manh Tran and Phan, Anh (2021) Linguistic-based Augmentation for Enhancing Vietnamese Sentiment Analysis. In: 15th RIVF International Conference on Computing and Communication Technologies, RIVF 2021, 2 December 2021through 4 December 2021, Hanoi.
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Identify customer's opinions about products, services, and brands bring many benefits to e-commerce development. Capturing customer attitudes helps retailers adjust business decisions. Customers can select the suitable product and the good service by consulting social experiences. However, free-style texts of customer feedback like acronyms, slang words, incorrect grammar, and so on are challenging any machine learning model. © 2021 IEEE.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Divisions: | Faculties > Faculty of Information Technology |
| Identification Number: | 10.1109/RIVF51545.2021.9642123 |
| Uncontrolled Keywords: | Sentiment analysis, Business decisions; Customer feedback; E-commerce development; Free style; Good services; Machine learning models; Product service; Sentiment analysis; Vietnamese, Sales |
| URI: | http://eprints.lqdtu.edu.vn/id/eprint/10293 |
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