Graph-Based Dependency Parsing is a dependency parsing approach that treats the task as a graph prediction problem, where the syntactic structure of a sentence is represented as a directed graph and optimal dependency trees are derived by scoring and selecting edges among all possible word pairs.
127
Publications
8.5K
Citations
298
Authors
138
Institutions
Publications per year
2017–2026
62
Parents
Publications
127
Relational Graph Attention Network for Aspect-based Sentiment Analysis
Kai Wang, Weizhou Shen, Yunyi Yang et al. · 2020 · 627 citations · Full text
Named Entity Recognition as Dependency Parsing
Juntao Yu, Bernd Bohnet, Massimo Poesio · 2020 · 449 citations · Full text
1–5 of 127
Authors
298
- JN
10
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- RM
8
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- YG
5
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- WS
5
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- XW
5
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1–5 of 298
Institutions
138
Google (United States)
Mountain View, United States
8 h-index
13 publications
1K citations
Uppsala University
Uppsala, Sweden
7 h-index
7 publications
659 citations
Stanford University
Stanford, United States
6 h-index
13 publications
2.2K citations
Peking University
Beijing, China
6 h-index
20 publications
715 citations
Carnegie Mellon University
Pittsburgh, United States
5 h-index
14 publications
602 citations
University of Stuttgart
Stuttgart, Germany
4 h-index
6 publications
250 citations
Soochow University
Suzhou, China
4 h-index
9 publications
428 citations
Kyoto University
Kyoto, Japan
4 h-index
9 publications
172 citations
1–8 of 138
Venues
- arXiv (Cornell University)
Repository · 10 publications · 1.5K citations
10
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- Transactions of the Association for Computational Linguistics
TACL · 6 publications · 695 citations
6
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- Computational Linguistics
4 publications · 190 citations
4
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- Proceedings of the AAAI Conference on Artificial Intelligence
Conference · 3 publications · 74 citations
3
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- IEEE/ACM Transactions on Audio Speech and Language Processing
TASLP · 3 publications · 46 citations
3
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1–5