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.
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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
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DOI: https://doi.org/10.1007/978-981-16-6624-7_14
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