Abstract
Text summarization is the technique for generating short and succinct summaries from long texts that focuses on the most important information but keeps the overall exhaustive signification of the whole text. This paper presents a method of generating short abstractive summaries from long Bengali news articles using some basic NLP approaches with various Recurrent Neural Network (RNN) architectures, such as Bidirectional RNN, Encoder-Decoder RNN, Sequence to Sequence (Seq2Seq) Learning with Attention mechanism, Longest Short-term Memory (LSTM), etc. Dataset collected by the authors from different Bengali online newspapers is used here. Then, the dataset is preprocessed. After that, word embedding and vocabulary counts are done. Finally, the deep learning approaches are applied to generate an abstractive summary for each news article. The model used the Seq2Seq algorithm with an attention mechanism which reduced the training loss up to 0.001 successfully. Another existing dataset is used to evaluate the results and found satisfactory results for own dataset than the other.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Wang L, Cardie C (2013) Domain-independent abstract generation for focused meeting summarization. In: Proceedings of the 51st annual meeting of the association for computational linguistics. Association for Computational Linguistics, Sofia, Bulgaria, pp. 1395–1405
Li C, Qian X, Liu Y (2013) Using supervised bigram-based ILP for extractive summarization. In: Proceedings of the 51st annual meeting of the association for computational linguistics. ACL, Sofia, Bulgaria, pp. 1004–1013
Qian X, Liu Y (2013) Fast joint compression and summarization via graph cuts. In: Proceedings of the conference on empirical methods in natural language processing. ACL, Seattle, Washington, USA, pp. 1492–1502
Bahdanau D, Cho K, Bengio Y (2014) Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473
Luong MT, Pham H, Manning CD (2015) Effective approaches to attention-based neural machine translation. arXiv preprint arXiv:1508.04025
Sutskever I, Vinyals O, Le QV (2014) Sequence to sequence learning with neural networks. In: Advances in neural information processing systems. NIPS, pp. 3104–3112
Liu PJ et al (2018) Generating wikipedia by summarizing long sequences. In: International conference on learning representation. arXiv:1801.10198
Shang L, Lu Z, Li H (2015) Neural responding machine for short-text conversation. In: Association for computational linguistics, vol 1. ACL, pp. 1577–1586
Abujar S, Hasan M, Shahin M, Hossain SA (2017) A heuristic approach of text summarization for Bengali documentation. In: 8th international conference on computing, communication and networking technologies. IEEE, pp. 1–8
Talukder MAI, Abujar S, Masum AKM, Faisal F, Hossain SA (2019) Bengali abstractive text summarization using sequence to sequence RNNs. In: 10th international conference on computing, communication and networking technologies. IEEE, pp. 1–5
Rahman MM, Pramanik MA, Sadik R, Roy M, Chakraborty P (2020) Bangla documents classification using transformer based deep learning models. In: 2nd international conference on sustainable technologies for industry 4.0. IEEE, Dhaka, Bangladesh, p. 15
Rahman S, Chakraborty P (2020) Bangla document classification using deep recurrent neural network with BiLSTM. In: Proceedings of international conference on machine intelligence and data science applications
Islam MJ, Ahmed K, Chowdhury MKH (2020) Summarizing online product reviews in Bengali based on similarity using sequence to sequence RNNs. In: 11th international conference on electrical and computer engineering. IEEE, Dhaka, Bangladesh
Bhattacharjee P, Mallick A, Islam MS, Jannat M (2020) Bengali abstractive news summarization (BANS): a neural attention approach. In: 2nd international conference on trends in computational and cognitive engineering. arXiv:2012.01747
Gulia S, Choudhury T (2016) An efficient automated design to generate UML diagram from natural language specifications. In: 6th international conference-cloud system and big data engineering (Confluence). IEEE, pp. 641–648
Chakraborty P, Ahmed S, Yousuf MA, Azad A, Alyami SA, Moni MA (2021) A human-robot interaction system calculating visual focus of human’s attention level. In: IEEE Access, vol. 9, pp. 93409–93421. https://doi.org/10.1109/ACCESS.2021.3091642
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Sultana, M., Chakraborty, P., Choudhury, T. (2022). Bengali Abstractive News Summarization Using Seq2Seq Learning with Attention. In: Tavares, J.M.R.S., Dutta, P., Dutta, S., Samanta, D. (eds) Cyber Intelligence and Information Retrieval. Lecture Notes in Networks and Systems, vol 291. Springer, Singapore. https://doi.org/10.1007/978-981-16-4284-5_24
Download citation
DOI: https://doi.org/10.1007/978-981-16-4284-5_24
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-16-4283-8
Online ISBN: 978-981-16-4284-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)