Gerson Zaverucha
Impact in
- Artificial Intelligence top 5%
- Topic Modeling
- Logic, Reasoning, and Knowledge
- Neural Networks and Applications
- Bayesian Modeling and Causal Inference
- Natural Language Processing Techniques
- Semantic Web and Ontologies
- Signal Processing top 10%
Papers in
-
- Neural Networks and Applications 11
- Logic, Reasoning, and Knowledge 10
- Bayesian Modeling and Causal Inference 9
- Topic Modeling 6
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- Data Mining Algorithms and Applications 7
- Co-authors
- Artur d’Avila Garcez (7 shared papers)Juliana Bernardes (5 shared papers)Alessandra Carbone (3 shared papers)Aline Paes (10 shared papers)Marta Mattoso (4 shared papers)Marcelo Teixeira (5 shared papers)Fernanda Baião (3 shared papers)Fabio Rocha Jimenez Vieira (1 shared paper)
- Journals
- Machine Learning (7 papers)BMC Bioinformatics (3 papers)Applied Intelligence (1 paper)Information Sciences (1 paper)Bioinformatics (1 paper)
- Partner nations
- BrazilUnited KingdomUnited States
In The Last Decade
Gerson Zaverucha
46 papers receiving 378 citations
Peers
Comparison fields: 5 of 75
- Artificial Intelligence 235
- Signal Processing 45
- Computational Theory and Mathematics 41
- Information Systems 57
- Software 8
Countries citing papers authored by Gerson Zaverucha
This map shows the geographic impact of Gerson Zaverucha'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 Gerson Zaverucha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gerson Zaverucha more than expected).
Fields of papers citing papers by Gerson Zaverucha
This network shows the impact of papers produced by Gerson Zaverucha. 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 Gerson Zaverucha. The network helps show where Gerson Zaverucha may publish in the future.
Co-authors
The 19 scholars most cited alongside Gerson Zaverucha, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1999 | 90 | |
| 2 | 2013 | 66 | |
| 3 | 2015 | 23 | |
| 4 | 2016 | 22 | |
| 5 | 1994 | 17 | |
| 6 | 2004 | 16 | |
| 7 | 2007 | 16 | |
| 8 | 2015 | 14 | |
| 9 | 2012 | 11 | |
| 10 | 2018 | 9 | |
| 11 | 2009 | 7 | |
| 12 | 2011 | 7 | |
| 13 | Fuzzy Bayes and Fuzzy Markov Predictors | 2002 | 7 |
| 14 | 2005 | 7 | |
| 15 | 2002 | 7 | |
| 16 | 1998 | 6 | |
| 17 | 2003 | 6 | |
| 18 | 2006 | 5 | |
| 19 | 2020 | 5 | |
| 20 | 2002 | 5 |
About Gerson Zaverucha
Gerson Zaverucha is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Computational Theory and Mathematics and Management Science and Operations Research, having authored 49 papers that have together received 405 indexed citations. Recurring topics across this work include Neural Networks and Applications (11 papers), Logic, Reasoning, and Knowledge (10 papers), Bayesian Modeling and Causal Inference (9 papers), Data Mining Algorithms and Applications (7 papers), Topic Modeling (6 papers), Rough Sets and Fuzzy Logic (6 papers), Energy Load and Power Forecasting (5 papers) and Data Quality and Management (5 papers). The work is most often cited by research in Artificial Intelligence (235 citations), Signal Processing (45 citations), Computational Theory and Mathematics (41 citations), Information Systems (57 citations) and Software (8 citations). Gerson Zaverucha has collaborated with scholars based in Brazil, United Kingdom and United States. Frequent co-authors include Artur d’Avila Garcez, Juliana Bernardes, Alessandra Carbone, Aline Paes, Marta Mattoso, Marcelo Teixeira, Fernanda Baião, Fabio Rocha Jimenez Vieira, Catherine Vaquero and Vı́tor Santos Costa. Their work appears in journals such as Machine Learning, BMC Bioinformatics, Applied Intelligence, Information Sciences and Bioinformatics.
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.