Integrating Topic-Aware Heterogeneous Graph Neural Network With Transformer Model for Medical Scientific Document Abstractive Summarization-Reference-Cited by-同舟云学术

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Integrating Topic-Aware Heterogeneous Graph Neural Network With Transformer Model for Medical Scientific Document Abstractive Summarization

Published:2024 Issue: Volume:12 Page:113855-113866
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Khaliq Ayesha¹^ORCID,Khan Atif²^ORCID,Afsar Awan Salman¹,Jan Salman³^ORCID,Umair Muhammad⁴^ORCID,Zuhairi Megat F.⁵^ORCID

Affiliation:

1. Department of Computer Science, University of Agriculture Faisalabad, Faisalabad, Pakistan

2. Department of Computer Science, Islamia College Peshawar, Peshawar, Khyber Pakhtunkhwa, Pakistan

3. Department of Information Technology, Al Buraimi University College, Al Buraimi, Oman

4. Department of Computer Science, City University of Science and Information Technology, Peshawar, Pakistan

5. Malaysian Institute of Information Technology, Universiti Kuala Lumpur, Kuala Lumpur, Malaysia

Funder

Malaysian Institute of Information Technology, Universiti Kuala Lumpur, Malaysia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10637403.pdf?arnumber=10637403

Reference57 articles.

1. Review of automatic text summarization techniques & methods

2. On Extractive and Abstractive Neural Document Summarization with Transformer Language Models

3. GATSum: Graph-Based Topic-Aware Abstract Text Summarization

4. Heterogeneous Graph Neural Networks for Extractive Document Summarization

5. SummaRuNNer: A Recurrent Neural Network Based Sequence Model for Extractive Summarization of Documents

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