Harnessing Deep Learning for Effective Extractive Text Summarization: A Comparative Study-Reference-Cited by-同舟云学术

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Harnessing Deep Learning for Effective Extractive Text Summarization: A Comparative Study

Published:2024-07-13 Issue: Volume:394 Page:581-588
ISSN:
Container-title:2024 Intelligent Methods, Systems, and Applications (IMSA)
language:
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Author:

Alsekait Deema mohammed¹,Almanaseer Waref²,Gomaa Ibrahim A³,Zeid Magdy Abd-Elghany³,Baligh Salma⁴,Alaa Hana⁴,Hegazy Jasmine⁴,Magdy Julia⁴,Eldmrat Alaa Tariq⁵,AbdElminaam Diaa Salama⁶

Affiliation:

1. Applied College, Princess Nourah Bint Abdulrahman University,Department of Computer Science and Information Technology,Saudi Arabia

2. Applied Science Private University,Faculty of Information Technology,Amman,Jordan,11931

3. Alobour high institute for computer and informatics,Computer Science Department,Cairo,Egypt

4. Misr International University,Faculty of Computer Science,Cairo,Egypt

5. Midocean University,Faculty of Human Sciences

6. Jadara University,Jadara Research Center,Irbid,Jordan,21110

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10651578/10651587/10652647.pdf?arnumber=10652647

Reference12 articles.

1. Extractive text summarization for scientific journal articles using long short-term memory and gated recurrent units

2. Text summarization for news articles by machine learning techniques;Hew Zi Jian;Applied Mathematics and Computational Intelligence,2022

3. Text Summarization Approaches Using Machine Learning & LSTM

4. Automatic Text Summarization Using a Machine Learning Approach

5. Deep learning in automatic text summarization;Gupta;International Journal of Computer Science and Information Security (IJCSIS),2018

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