Proposing Appropriate SMS Spam Detection Approaches for Variations of the Vietnamese Language
Vu Minh Tuan, Do Thuy Duong, Tran Quang Anh · 2023
This paper introduces suitable methods for detecting SMS spam in various forms of the Vietnamese language. The researchers conducted experiments using five algorithms: SVM, Naive Bayes, Random Forests, CNN, and LSTM, across three different Vietnamese datasets. The results indicate that LSTM and CNN, complemented by a transformer learning model called PhoBert, outperformed traditional machine learning models. Specifically, the LSTM model achieved the highest accuracy of 97.77% when applied to the Vietnamese dataset with full diacritics. Similarly, the CNN model and PhoBert model achieved the highest accuracy of 95.56% when working with the Vietnamese dataset without diacritics.