Multi-Document Summarization is a text summarization approach that generates a concise and coherent summary by synthesizing information from multiple distinct documents on a related topic, distinguishing it from single-document summarization through its integration of cross-document content and redundancy management.
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2017–2026
199
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660
Automatic text summarization: A comprehensive survey
Wafaa S. El-Kassas, Cherif Salama, Ahmed Rafea et al. · Expert Systems with Applications · 2020 · 795 citations
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Columbia University
New York, United States
28 h-index
82 publications
9.8K citations
Peking University
Beijing, China
27 h-index
82 publications
5.3K citations
University of Michigan
Ann Arbor, United States
15 h-index
30 publications
4.9K citations
Hong Kong Polytechnic University
Hong Kong, Hong Kong
13 h-index
44 publications
2.2K citations
Florida International University
Miami, United States
13 h-index
33 publications
2.2K citations
Carnegie Mellon University
Pittsburgh, United States
13 h-index
24 publications
2K citations
University of Lethbridge
Lethbridge, Canada
11 h-index
21 publications
631 citations
University of Pennsylvania
Philadelphia, United States
11 h-index
18 publications
1K citations
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- Expert Systems with Applications
23 publications · 2K citations
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- arXiv (Cornell University)
Repository · 28 publications · 1.3K citations
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- Information Processing & Management
13 publications · 1.8K citations
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- Proceedings of the AAAI Conference on Artificial Intelligence
Conference · 13 publications · 697 citations
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- International Conference on Computational Linguistics
Conference · 10 publications · 352 citations
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