Abstract
With the advancement of technology, text is abundant in today’s world, especially on the web. Therefore, it is important to summarize the text so that it becomes easier to read and understand while maintaining the essence and context of the information. Automatic text summarization is an effective way of finding relevant and important information precisely in large text in a short amount of time with little efforts. In this paper, we propose a text summarization model using NLP techniques that can understand the context of the entire text, identify the most important portions of the text, and generate coherent summaries.
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Ramesh, G.S., Vamsi Manyam, Vijoosh Mandula, Pavan Myana, Sathvika Macha, Suprith Reddy (2022). Abstractive Text Summarization Using T5 Architecture. In: Reddy, A.B., Kiranmayee, B., Mukkamala, R.R., Srujan Raju, K. (eds) Proceedings of Second International Conference on Advances in Computer Engineering and Communication Systems. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-7389-4_52
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DOI: https://doi.org/10.1007/978-981-16-7389-4_52
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