Neural Attention Model for Abstractive Text Summarization Using Linguistic Feature Space-Reference-Cited by-同舟云学术

Neural Attention Model for Abstractive Text Summarization Using Linguistic Feature Space

Published:2023 Issue: Volume:11 Page:23557-23564
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Dilawari Aniqa¹,Khan Muhammad Usman Ghani²^ORCID,Saleem Summra³,Zahoor-Ur-Rehman ⁴^ORCID,Shaikh Fatema Sabeen⁵^ORCID

Affiliation:

1. Department of Computer Science and Information Technology, University of Home Economics, Lahore, Pakistan

2. Department of Computer Science, University of Engineering and Technology, Lahore (UET Lahore), Lahore, Pakistan

3. Rheinland-Pfälzische Technische Universität, Kaiserslautern, Kaiserslautern, Germany

4. Department of Computer Science, COMSATS University Islamabad, Attock Campus, Attock, Pakistan

5. Computer Information Systems Department, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10054384.pdf?arnumber=10054384

Reference38 articles.

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2. Topiary;zajic;Proc HLT-NAACL Document Understand Workshop,2004

3. A Unified Model for Extractive and Abstractive Summarization using Inconsistency Loss

4. Multi-Orientation Scene Text Detection with Adaptive Clustering

5. Sentence reduction for automatic text summarization

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