André Nascimento
Impact in
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- Computational Drug Discovery Methods
Papers in
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- Natural Language Processing Techniques 6
- Topic Modeling 6
- Machine Learning and Data Classification 4
- Advanced Text Analysis Techniques 3
- Metaheuristic Optimization Algorithms Research 3
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- Online and Blended Learning 3
- Co-authors
- Ricardo B. C. Prudêncio (10 shared papers)Ivan G. Costa (3 shared papers)Rafael Ferreira Mello (24 shared papers)Péricles Miranda (24 shared papers)Dragan Gašević (7 shared papers)Tapas Si (5 shared papers)Marcílio C. P. de Souto (1 shared paper)Katerina Mangaroska (1 shared paper)
In The Last Decade
André Nascimento
40 papers receiving 383 citations
Peers
Comparison fields: 5 of 82
- Computational Theory and Mathematics 156
- Health Informatics 8
- Computer Science Applications 33
- Artificial Intelligence 112
- Molecular Biology 153
Countries citing papers authored by André Nascimento
This map shows the geographic impact of André Nascimento'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 André Nascimento with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites André Nascimento more than expected).
Fields of papers citing papers by André Nascimento
This network shows the impact of papers produced by André Nascimento. 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 André Nascimento. The network helps show where André Nascimento may publish in the future.
Co-authors
The 25 scholars most cited alongside André Nascimento, 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 48 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 189 | |
| 2 | 2020 | 25 | |
| 3 | 2009 | 19 | |
| 4 | 2018 | 16 | |
| 5 | 2020 | 15 | |
| 6 | 2021 | 13 | |
| 7 | 2021 | 12 | |
| 8 | 2019 | 10 | |
| 9 | 2024 | 10 | |
| 10 | 2023 | 8 | |
| 11 | 2021 | 8 | |
| 12 | 2020 | 7 | |
| 13 | 2022 | 7 | |
| 14 | Group Profiling for Understanding Educational Social Networking. | 2013 | 4 |
| 15 | 2021 | 4 | |
| 16 | 2022 | 4 | |
| 17 | 2023 | 3 | |
| 18 | 2022 | 3 | |
| 19 | 2023 | 3 | |
| 20 | 2009 | 3 |
About André Nascimento
André Nascimento is a scholar working on Artificial Intelligence, Education, Information Systems, Molecular Biology and Computational Theory and Mathematics, having authored 48 papers that have together received 396 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (6 papers), Topic Modeling (6 papers), Innovative Teaching and Learning Methods (4 papers), Machine Learning and Data Classification (4 papers), Online and Blended Learning (3 papers), Artificial Intelligence in Law (3 papers), Advanced Text Analysis Techniques (3 papers) and Metaheuristic Optimization Algorithms Research (3 papers). The work is most often cited by research in Computational Theory and Mathematics (156 citations), Health Informatics (8 citations), Computer Science Applications (33 citations), Artificial Intelligence (112 citations) and Molecular Biology (153 citations). André Nascimento has collaborated with scholars based in Brazil, Australia and India. Frequent co-authors include Ricardo B. C. Prudêncio, Ivan G. Costa, Rafael Ferreira Mello, Péricles Miranda, Dragan Gašević, Tapas Si, Marcílio C. P. de Souto, Katerina Mangaroska, Anderson Pinheiro Cavalcanti and Fred Freitas. Their work appears in journals such as Expert Systems with Applications, Artificial Intelligence Review, IEEE Transactions on Learning Technologies, BMC Bioinformatics and Lecture notes in computer science.
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.