Renata Vieira

3.8k citations
165 papers · 1.7k indexed · h-index 21

Renata Vieira

146 papers receiving 1.5k citations

Peers

Renata Vieira
Comparison fields: 5 of 133
  • Artificial Intelligence 999
  • Surgery 315
  • Information Systems 177
  • Radiology, Nuclear Medicine and Imaging 169
  • Rheumatology 159
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Citations per field
00.5×3.4×
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Citations per year

Countries citing papers authored by Renata Vieira

Since Specialization
Citations

This map shows the geographic impact of Renata Vieira'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 Renata Vieira with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Renata Vieira more than expected).

Fields of papers citing papers by Renata Vieira

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Renata Vieira. 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 Renata Vieira. The network helps show where Renata Vieira may publish in the future.

Co-authorship network of co-authors of Renata Vieira

This figure shows the co-authorship network connecting the top 25 collaborators of Renata Vieira. A scholar is included among the top collaborators of Renata Vieira 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 Renata Vieira. Renata Vieira is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 4
3 0
4 9
5 1
6 8
7 11
8
Adapting an entity centric model for Portuguese coreference resolution
1
9
An Ontology-based Mobile Application for Task Managing in Collaborative Groups
6
10
Dealing With Imbalanced Datasets For Coreference Resolution
3
11 10
12 9
13 5
14
A Framework for Multilingual Ontology Mapping
24
15 34
16
Desafios do processamento de línguas naturais
2
17
Proceedings of the 10th international conference on Computational Processing of the Portuguese Language
6
18
A REVIEW OF THE LINGUISTIC RESEARCH ON DEFINITE DESCRIPTIONS
1
19 3
20 16

About Renata Vieira

Renata Vieira is a scholar working on Artificial Intelligence, Issues, ethics and legal aspects and Health Information Management, having authored 165 papers that have together received 1.7k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (59 papers), Topic Modeling (45 papers) and Semantic Web and Ontologies (40 papers). The work is most often cited by research in Artificial Intelligence (999 citations), Orthopedics and Sports Medicine (155 citations) and Rheumatology (159 citations). Renata Vieira has collaborated with scholars based in Brazil, United States and Portugal. Frequent co-authors include Massimo Poesio, Zehava Sadka Rosenberg, Rafael H. Bordini, Simone Teufel, Leon Rybak, Ravinder R. Regatte, Cássia Trojahn dos Santos, Conrado Furtado Albuquerque Cavalcanti, Luca Maria Sconfienza and Catherine Petchprapa. Their work appears in journals such as SHILAP Revista de lepidopterología, International Journal of Environmental Research and Public Health and American Journal of Roentgenology.

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.

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