Bangla Text Generation Using Bidirectional Optimized Gated Recurrent Unit Network
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Publisher
Springer Singapore
Link
http://link.springer.com/content/pdf/10.1007/978-981-33-4673-4_9
Reference21 articles.
1. Abujar, S., Masum, A.K.M., Chowdhury, S.M.M.H., Hasan, M., Hossain, S.A.: Bengali Text generation using bi-directional RNN. In: 2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT), July 2019, pp. 1–5
2. Islam, M., Sultana Sharmin, S., Abujar, S.,Hossain, S.: Sequence-to- sequence Bangla sentence generation with LSTM recurrent neural networks. Procedia Comput Sci 152 (2019)
3. Rakib, O.F., Akter, S., Khan, M.A., Das, A.K., Habibullah, K.M.: Bangla word prediction and sentence completion using GRU: an extended version of RNN on N-gram language model. In: 2019 International Conference on Sustainable Technologies for Industry 4.0 (STI), pp. 1–6, Dec 2019
4. Islam, S., et al.: Bangla sentence correction using deep neural network based sequence to sequence learning, pp. 1–6, Dec 2018
5. Song, S., Huang, H., Ruan, T.: Abstractive text summarization using LSTM-CNN based deep learning. Multimedia Tools Appl. 78, 857–875 (2020). ISSN: 1573-7721. https://doi.org/10.1007/s11042-018-5749-3
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