HYBRID INTEGRATION OF BERT AND BILSTM MODELS FOR SENTIMENT ANALYSIS
The rapid growth of sentiment analysis research has driven increasing interest in deep learning models, particularly transformer-based architectures such as BERT and recurrent neural networks like BiLSTM. While both approaches have shown substantial success in text classification tasks, each presen...
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| Главные авторы: | , , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Universitas Pattimura
2026-01-01
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| Серии: | Barekeng |
| Предметы: | |
| Online-ссылка: | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/21419 |
| Метки: |
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