Rule-Based Summarization is a summarization approach that systematically generates condensed texts by applying predefined linguistic, syntactic, or discourse rules to identify and extract salient information from source documents.
54
Publications
3K
Citations
153
Authors
78
Institutions
Publications per year
2017–2026
15
Parents
Publications
54
Neural Latent Extractive Document Summarization
Xingxing Zhang, Mirella Lapata, Furu Wei et al. · 2018 · 170 citations · Full text
Direct Instruction of Summarization Skills
Victoria Chou Hare, Kathleen M. Borchardt · Reading Research Quarterly · 1984 · 142 citations
Education, Instruction, Teaching +16
1–5 of 54
Authors
153
- JK
3
h-index
- SZ
3
h-index
- BH
2
h-index
- CK
2
h-index
- CG
2
h-index
1–5 of 153
Institutions
78
Polish Academy of Sciences
Warsaw, Poland
3 h-index
5 publications
376 citations
University of Edinburgh
Edinburgh, United Kingdom
3 h-index
8 publications
491 citations
Universitat Pompeu Fabra
Barcelona, Spain
2 h-index
5 publications
150 citations
George Mason University
Fairfax, United States
2 h-index
2 publications
29 citations
Columbia University
New York, United States
2 h-index
4 publications
134 citations
University of Southern California
Los Angeles, United States
2 h-index
5 publications
383 citations
Universidad de Granada
Granada, Spain
2 h-index
5 publications
225 citations
Comilla University
Comilla, Bangladesh
1 h-index
2 publications
90 citations
1–8 of 78
Venues
- IEEE Access
2 publications · 52 citations
2
h-index
- International Journal of Software Science and Computational Intelligence
IJSSCI · 1 publications · 38 citations
1
h-index
- Journal of Ambient Intelligence and Humanized Computing
1 publications · 25 citations
1
h-index
- Proceedings of 6th International Fuzzy Systems Conference
Conference · 1 publications · 13 citations
1
h-index
- Data Science and Engineering
1 publications · 18 citations
1
h-index
1–5