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Vui lòng dùng định danh này để trích dẫn hoặc liên kết đến tài liệu này:
https://elib.vku.udn.vn/handle/123456789/2352
Nhan đề: | A Study on Vietnamese Semantic Analysis using BERT-Based PreTrained Language Model |
Tác giả: | Pham, Vu Thu Nguyet Ha, Thi Minh Phuong |
Từ khoá: | Natural Language Processing Sentiment Analysis Vietnamese Deep Learning |
Năm xuất bản: | thá-2022 |
Nhà xuất bản: | Da Nang Publishing House |
Tóm tắt: | One of the most significant NLP tasks is sentiment analysis, in which machine learning models are taught to identify text based on polarity of opinion. Many suggested models have produced cutting-edge results for sentiment analysis in English corpora. However, there have not been many investigations of this technique for Vietnamese corpus, which has resulted in several limitations in Vietnamese study. In this paper, we suggested a sentiment analysis technique for Vietnamese utilizing the PhoBERT pretrained model. PhoBERT is based on RoBERTa, a robust Vietnamese optimization of the well-known BERT model. Our technique produces quite good performance on the given dataset with an AUC score of 86%. This is anticipated to provide the groundwork for future study in Vietnamese, which is a language with limited resources. |
Mô tả: | The 11th Conference on Information Technology and its Applications; Poster; pp. 30-37. |
Định danh: | http://elib.vku.udn.vn/handle/123456789/2352 |
Bộ sưu tập: | CITA 2022 |
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