Natalia Silveira
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 10%
- Language and Linguistics top 5%
- Information Systems top 10%
- Molecular Biology
- Co-authors
- Christopher D. ManningMarie-Catherine de MarneffeFilip GinterJoakim NivreTimothy DozatRyan McDonaldSampo PyysaloJan Hajič
- Topics
- Natural Language Processing Techniques (6 papers)Topic Modeling (6 papers)Semantic Web and Ontologies (4 papers)
- Journals
- Language Resources and EvaluationDigital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B))Workshop on Statistical Machine Translation
- Partner nations
- United StatesSwedenBrazil
In The Last Decade
Natalia Silveira
7 papers receiving 837 citations
Hit Papers
Peers
Comparison fields: 5 of 68
- Artificial Intelligence 901
- Computer Vision and Pattern Recognition 96
- Language and Linguistics 86
- Information Systems 75
- Molecular Biology 40
Countries citing papers authored by Natalia Silveira
This map shows the geographic impact of Natalia Silveira's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Natalia Silveira with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Natalia Silveira more than expected).
Fields of papers citing papers by Natalia Silveira
This network shows the impact of papers produced by Natalia Silveira. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Natalia Silveira. The network helps show where Natalia Silveira may publish in the future.
Co-authorship network of co-authors of Natalia Silveira
This figure shows the co-authorship network connecting the top 25 collaborators of Natalia Silveira. A scholar is included among the top collaborators of Natalia Silveira based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Natalia Silveira. Natalia Silveira is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | Universal Dependencies v1: A Multilingual Treebank Collectionbreakdown → | 575 |
| 3 | Does Universal Dependencies need a parsing representation? An investigation of English | 7 |
| 4 | Universal Stanford dependencies: A cross-linguistic typology | 255 |
| 5 | TRATAMENTOS FISIOTERAPÊUTICOS NA OSTEOARTROSE DE JOELHO: UMA REVISÃO | 1 |
| 6 | A Gold Standard Dependency Corpus for English | 109 |
| 7 | Feature-Rich Phrase-based Translation: Stanford University's Submission to the WMT 2013 Translation Task | 5 |
| 8 | More Constructions, More Genres: Extending Stanford Dependencies | 20 |
About Natalia Silveira
Natalia Silveira is a scholar working on General Dentistry, Artificial Intelligence and Health, having authored 8 papers that have together received 972 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (6 papers), Topic Modeling (6 papers) and Semantic Web and Ontologies (4 papers). The work is most often cited by research in Artificial Intelligence (901 citations), Language and Linguistics (86 citations) and Computer Vision and Pattern Recognition (96 citations). Natalia Silveira has collaborated with scholars based in United States, Sweden and Brazil. Frequent co-authors include Christopher D. Manning, Marie-Catherine de Marneffe, Filip Ginter, Joakim Nivre, Timothy Dozat, Ryan McDonald, Sampo Pyysalo, Jan Hajič, Slav Petrov and Daniel Zeman. Their work appears in journals such as Language Resources and Evaluation, Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)) and Workshop on Statistical Machine Translation.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.