Citation :

A.Udaya Kumar, B.Roshini, K.Mounika, B.Tejaswini, B.Y.Sahitya, 2023. "Automatic Text Summarization Using Deep Learning" ESP International Journal of Advancements in Computational Technology (ESP-IJACT)  Volume 1, Issue 2: 40-48.

Abstract :

Text summarising is a method for taking the most crucial information from various texts, compressing it, and keeping the text's overall meaning. Rarely does one need to read reams of documentation to get the gist of a topic; frequently, a brief synopsis is adequate. Automatic Text Summarization (ATS) can be useful in this situation by compressing the text and gathering important information in one place. Only the important sentences from the original document are recognized by the extraction techniques and extracted from the text. As a result, it is more difficult when using abstractive summarization approaches, which create the summary after reading the original text. In this paper, we implemented text summarization using the t5 algorithm and evaluated it based on different criteria, such as the amount of compression or summarization, the amount of meaning lost, and the number of grammatical errors. We also made sure that the information we got from the output was accurate and useful.

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Keywords :

Natural Language Processing, T5 Model, Feature Extraction.