Skip to main content

Summarizing Bengali Text: An Extractive Approach

  • Conference paper
  • First Online:
Intelligent Data Engineering and Analytics

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 266))

Abstract

Text summarization is a challenging task in the field of Natural Language Processing. In the case of lower resource language like Bengali is also a difficult task to make an automatic text summarization system. This paper is based on the extractive summarization of Bengali text. Text summarization deletes the less useful information in a piece of text or a paragraph and summarizes it into a confined text. This helps in finding the required text more effectively and quickly. There are many types of algorithms used for summarizing the text. Here in this paper, we have used TF-IDF and BERT-SUM technologies for the Bengali extractive text summarization.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Christian, H., Agus, M.P., Suhartono, D.: Single document automatic text summarization using term frequency-inverse document frequency (tf-idf). ComTech Comput. Math. Eng. Appl. 7(4), 285–294 (2016)

    Google Scholar 

  2. Sarkar, K.: An approach to summarizing bengali news documents. In: Proceedings of the International Conference on Advances in Computing, Communications and Informatics. pp. 857–862 (2012)

    Google Scholar 

  3. Bharti, S.K., Babu, K.S.: Automatic keyword extraction for text summarization: a survey. arXiv preprint arXiv:1704.03242 (2017)

  4. Asa, A.S., Akter, S., Uddin, M.P., Hossain, M.D., Roy, S.K., Afjal, M.I.: A comprehensive survey on extractive text summarization techniques. Am. J. Eng. Res. 6(1), 226–239 (2017)

    Google Scholar 

  5. Abujar, S., Hasan, M., Shahin, M., Hossain, S.A.: A heuristic approach of text summarization for bengali documentation. In: 2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT). pp. 1–8. IEEE (2017)

    Google Scholar 

  6. Pattnaik, P., Mallick, D.K., Parida, S., Dash, S.R.: Extractive odia text summarization system: An ocr based approach. In: International Conference on Biologically Inspired Techniques in Many-Criteria Decision Making. pp. 136–143. Springer (2019)

    Google Scholar 

  7. Liu, Y.: Fine-tune bert for extractive summarization. arXiv preprint arXiv:1903.10318 (2019)

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Satya Ranjan Dash .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Dash, S.R., Guha, P., Mallick, D.K., Parida, S. (2022). Summarizing Bengali Text: An Extractive Approach. In: Satapathy, S.C., Peer, P., Tang, J., Bhateja, V., Ghosh, A. (eds) Intelligent Data Engineering and Analytics. Smart Innovation, Systems and Technologies, vol 266. Springer, Singapore. https://doi.org/10.1007/978-981-16-6624-7_14

Download citation

Publish with us

Policies and ethics