BiDAF model in sentiment analysis task
Sentiment analysis is a critical job in natural language processing. Controlling and evaluating customer feedback on their goods is a task that companies are especially interested in. For reading comprehension problems including attention processes, the BiDAF model is developed. Attention processes...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Trường Đại học Vinh
2023-06-01
|
| Series: | Tạp chí Khoa học |
| Subjects: | |
| Online Access: | https://vujs.vn//api/view.aspx?cid=2ef878d2-acf7-43fe-80cd-2b64262a3ef8 |
| _version_ | 1797789281814577152 |
|---|---|
| author | Luong Thi Minh Hue |
| author_facet | Luong Thi Minh Hue |
| author_sort | Luong Thi Minh Hue |
| collection | DOAJ |
| description | Sentiment analysis is a critical job in natural language processing. Controlling and evaluating customer feedback on their goods is a task that companies are especially interested in. For reading comprehension problems including attention processes, the BiDAF model is developed. Attention processes
have recently been expanded and effectively used for natural language processing problems. In this study, we use the BiDAF model to perform sentiment analysis on Amazon product evaluations at the sentence level. The BiDAF model is a multilayered processing model that reflects context at multiple levels and uses the BiLSTM model. Furthermore, we investigate the sentence's attention weight distribution using the attention mechanism. With a recall measure, the model achieves an accuracy of up to 99.9%. We discovered that the attention weights of important phrases are equivalent to, if not higher
than, the attention weights of sentiment words in the sentence. |
| first_indexed | 2024-03-13T01:48:23Z |
| format | Article |
| id | doaj.art-53f42bc5af7949e5b97753608c26731b |
| institution | Directory Open Access Journal |
| issn | 1859-2228 |
| language | English |
| last_indexed | 2024-03-13T01:48:23Z |
| publishDate | 2023-06-01 |
| publisher | Trường Đại học Vinh |
| record_format | Article |
| series | Tạp chí Khoa học |
| spelling | doaj.art-53f42bc5af7949e5b97753608c26731b2023-07-03T02:12:41ZengTrường Đại học VinhTạp chí Khoa học1859-22282023-06-01522A172310.56824/vujs.2023a021BiDAF model in sentiment analysis taskLuong Thi Minh Hue0University of Information and Communication Technology, Thai Nguyen University, VietnamSentiment analysis is a critical job in natural language processing. Controlling and evaluating customer feedback on their goods is a task that companies are especially interested in. For reading comprehension problems including attention processes, the BiDAF model is developed. Attention processes have recently been expanded and effectively used for natural language processing problems. In this study, we use the BiDAF model to perform sentiment analysis on Amazon product evaluations at the sentence level. The BiDAF model is a multilayered processing model that reflects context at multiple levels and uses the BiLSTM model. Furthermore, we investigate the sentence's attention weight distribution using the attention mechanism. With a recall measure, the model achieves an accuracy of up to 99.9%. We discovered that the attention weights of important phrases are equivalent to, if not higher than, the attention weights of sentiment words in the sentence. https://vujs.vn//api/view.aspx?cid=2ef878d2-acf7-43fe-80cd-2b64262a3ef8natural language processinglstmdeep learningmachine learningbidaf |
| spellingShingle | Luong Thi Minh Hue BiDAF model in sentiment analysis task Tạp chí Khoa học natural language processing lstm deep learning machine learning bidaf |
| title | BiDAF model in sentiment analysis task |
| title_full | BiDAF model in sentiment analysis task |
| title_fullStr | BiDAF model in sentiment analysis task |
| title_full_unstemmed | BiDAF model in sentiment analysis task |
| title_short | BiDAF model in sentiment analysis task |
| title_sort | bidaf model in sentiment analysis task |
| topic | natural language processing lstm deep learning machine learning bidaf |
| url | https://vujs.vn//api/view.aspx?cid=2ef878d2-acf7-43fe-80cd-2b64262a3ef8 |
| work_keys_str_mv | AT luongthiminhhue bidafmodelinsentimentanalysistask |