Deep learning based sequence to sequence model for abstractive telugu text summarization
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-022-14099-x.pdf
Reference43 articles.
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2. Alquliti WH, Abdul Ghani NB (2019) Convolutional neural network based for automatic text summarization. Int J Advan Comput Sci Applic (IJACSA) 10(4). https://doi.org/10.14569/IJACSA.2019.0100424
3. Bahdanau D, Cho K, Bengio Y (2014) Neural machine translation by jointly learning to align and translate. ArXiv:1409–0473
4. Bengio Y, Simard P, Frasconi P (1994) Learning long-term dependencies with gradient descent is difficult. IEEE Trans Neural Netw 5(2):157–166. https://doi.org/10.1109/72.279181
5. Chung J, Gulcehre C, Cho K and Bengio Y (2014) Empirical evaluation of gated recurrent neural networks on sequence modeling In NIPS 2014 Workshop on Deep Learning: https://doi.org/10.1109/TVCG.2013.272
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