Multidocument Aspect Classification for Aspect-Based Abstractive Summarization-Reference-Cited by-同舟云学术

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Multidocument Aspect Classification for Aspect-Based Abstractive Summarization

Published:2024-02 Issue:1 Volume:11 Page:1483-1492
ISSN:2329-924X
Container-title:IEEE Transactions on Computational Social Systems
language:
Short-container-title:IEEE Trans. Comput. Soc. Syst.

Author:

Wang Ye¹^ORCID,Zhou Yingmin²,Wang Mengzhu¹^ORCID,Chen Zhenghan³^ORCID,Cai Zhiping¹^ORCID,Chen Junyang⁴^ORCID,Leung Victor C. M.⁴^ORCID

Affiliation:

1. College of Computer, National University of Defense Technology, Changsha, China

2. Baidu Inc., Beijing, China

3. School of Software and Microelectronics, Peking University, Beijing, China

4. College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China

Funder

National Natural Science Foundation of China

Science and Technology Innovation Program of Hunan Province

Open Research Fund from Guangdong Laboratory of Artificial Intelligence and Digital Economy [Shenzhen (SZ)]

Natural Science Foundation of Guangdong Province of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Human-Computer Interaction,Social Sciences (miscellaneous),Modeling and Simulation

Link

http://xplorestaging.ieee.org/ielx7/6570650/10414252/10068329.pdf?arnumber=10068329

Reference45 articles.

1. A Neural Attention Model for Abstractive Sentence Summarization

2. Abstractive Summarization Model with a Feature-Enhanced Seq2Seq Structure

3. Get To The Point: Summarization with Pointer-Generator Networks

4. Don’t Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization

5. Multi-Granularity Interaction Network for Extractive and Abstractive Multi-Document Summarization

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