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What we achieve on text extractive summarization based on graph?

Authors :
Shuang Chen
Tao Ren
Ying Qv
Yang Shi
Source :
Journal of Intelligent & Fuzzy Systems. 2022, Vol. 43 Issue 6, p7057-7065. 9p.
Publication Year :
2022

Abstract

Dealing with the explosive growth of web sources on the Internet requires the use of efficient systems. Automatic text summarization is capable of addressing this issue. Recent years have seen remarkable success in the use of graph theory on text extractive summarization. However, the understanding of why and how they perform so well is still not clear. In this paper, we intend to seek a better understanding of graph models, which can benefit from graph extractive summarization. Additionally, analysis has been performed qualitatively with the graph models in the design of recent graph extractive summarization. Based on the knowledge acquired from the survey, our work could provide more clues for future research on extractive summarization. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10641246
Volume :
43
Issue :
6
Database :
Academic Search Index
Journal :
Journal of Intelligent & Fuzzy Systems
Publication Type :
Academic Journal
Accession number :
160553602
Full Text :
https://doi.org/10.3233/JIFS-220433