GRENZE International Journal of Engineering and Technology
Vol. 9
(2023), Issue 1
An Automatic Extractive Text Summarization
Authors
Meet Bedhmutha, Dipti Sakhare, Chandan Yadav, Devashish Dani, Kshitij Patil
Abstract
In this new era of artificial intelligence and automation there is outburst in amount of data. It is challenging for a person to dig into the content and bring the light on essential data. So, for such complexity there is need of developing a perfunctory task of automatic and precise text summary of data. Automatic text summarizer reduces reading time and make selection process easier. In recent years, there has been a little change in the text summarising research trend as well. New trends have evolved that show how to improve text summarization performance and achieve high accuracy. Hence, this project mainly focuses on designing an extractive summarizer of English text/document which generate abbreviated summary with the help of different algorithms.
Pages:
2881 - 2886