A novel BiGRUBiLSTM model for Multilevel Sentiment Analysis Using Deep Neural Network with BiGRU-BiLSTM
In multilevel sentiment classification task, there is a challenging task of limited coherence, contextual and semantic information. This paper proposes a new hybrid deep learning architecture for multilevel text sentiment classification with less training and simple network structure for better perf...
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| Format: | Conference or Workshop Item |
| Language: | English |
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Springer Singapore
2021
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| Online Access: | http://umpir.ump.edu.my/id/eprint/33280/ http://umpir.ump.edu.my/id/eprint/33280/1/A%20novel%20BiGRUBiLSTM%20model%20for%20multilevel%20sentiment%20analysis%20using%20deep%20neural%20network%20with%20BiGRU-%20BiLSTM.pdf |
| _version_ | 1848824216926814208 |
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| author | Islam, Md Shofiqul Ngahzaifa, Ab. Ghani |
| author_facet | Islam, Md Shofiqul Ngahzaifa, Ab. Ghani |
| author_sort | Islam, Md Shofiqul |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | In multilevel sentiment classification task, there is a challenging task of limited coherence, contextual and semantic information. This paper proposes a new hybrid deep learning architecture for multilevel text sentiment classification with less training and simple network structure for better performance and can handle the implicit semantic information and contextual meaning of text. In this research the proposed hybrid deep neural network architecture made with Bidirectional Gated Recurrent Unit (BiGRU) and Bi-Directional Long Term Short Memory(BiLSTM) of Recurrent Neural Network (RNN) for multilevel text sentiment classification and this performs better with higher accuracy than other methods compared. This proposed method BiGRUBiLSTM model outperformed the traditional machine learning methods and the compared deep learning models with about average of 1% margin accuracy on different datasets. |
| first_indexed | 2025-11-15T03:09:31Z |
| format | Conference or Workshop Item |
| id | ump-33280 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:09:31Z |
| publishDate | 2021 |
| publisher | Springer Singapore |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-332802022-01-25T03:18:23Z http://umpir.ump.edu.my/id/eprint/33280/ A novel BiGRUBiLSTM model for Multilevel Sentiment Analysis Using Deep Neural Network with BiGRU-BiLSTM Islam, Md Shofiqul Ngahzaifa, Ab. Ghani QA75 Electronic computers. Computer science QA76 Computer software In multilevel sentiment classification task, there is a challenging task of limited coherence, contextual and semantic information. This paper proposes a new hybrid deep learning architecture for multilevel text sentiment classification with less training and simple network structure for better performance and can handle the implicit semantic information and contextual meaning of text. In this research the proposed hybrid deep neural network architecture made with Bidirectional Gated Recurrent Unit (BiGRU) and Bi-Directional Long Term Short Memory(BiLSTM) of Recurrent Neural Network (RNN) for multilevel text sentiment classification and this performs better with higher accuracy than other methods compared. This proposed method BiGRUBiLSTM model outperformed the traditional machine learning methods and the compared deep learning models with about average of 1% margin accuracy on different datasets. Springer Singapore 2021-07-16 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/33280/1/A%20novel%20BiGRUBiLSTM%20model%20for%20multilevel%20sentiment%20analysis%20using%20deep%20neural%20network%20with%20BiGRU-%20BiLSTM.pdf Islam, Md Shofiqul and Ngahzaifa, Ab. Ghani (2021) A novel BiGRUBiLSTM model for Multilevel Sentiment Analysis Using Deep Neural Network with BiGRU-BiLSTM. In: Recent Trends in Mechatronics Towards Industry 4.0: Selected Articles from iM3F 2020, Malaysia , 6 August 2020 , Universiti Malaysia Pahang (Virtual). pp. 403-414., 730. ISBN 978-981-33-4597-3 (Published) https://doi.org/10.1007/978-981-33-4597-3_37 https://doi.org/10.1007/978-981-33-4597-3_37 |
| spellingShingle | QA75 Electronic computers. Computer science QA76 Computer software Islam, Md Shofiqul Ngahzaifa, Ab. Ghani A novel BiGRUBiLSTM model for Multilevel Sentiment Analysis Using Deep Neural Network with BiGRU-BiLSTM |
| title | A novel BiGRUBiLSTM model for Multilevel Sentiment Analysis Using Deep Neural Network with BiGRU-BiLSTM |
| title_full | A novel BiGRUBiLSTM model for Multilevel Sentiment Analysis Using Deep Neural Network with BiGRU-BiLSTM |
| title_fullStr | A novel BiGRUBiLSTM model for Multilevel Sentiment Analysis Using Deep Neural Network with BiGRU-BiLSTM |
| title_full_unstemmed | A novel BiGRUBiLSTM model for Multilevel Sentiment Analysis Using Deep Neural Network with BiGRU-BiLSTM |
| title_short | A novel BiGRUBiLSTM model for Multilevel Sentiment Analysis Using Deep Neural Network with BiGRU-BiLSTM |
| title_sort | novel bigrubilstm model for multilevel sentiment analysis using deep neural network with bigru-bilstm |
| topic | QA75 Electronic computers. Computer science QA76 Computer software |
| url | http://umpir.ump.edu.my/id/eprint/33280/ http://umpir.ump.edu.my/id/eprint/33280/ http://umpir.ump.edu.my/id/eprint/33280/ http://umpir.ump.edu.my/id/eprint/33280/1/A%20novel%20BiGRUBiLSTM%20model%20for%20multilevel%20sentiment%20analysis%20using%20deep%20neural%20network%20with%20BiGRU-%20BiLSTM.pdf |