Cláudia Antunes
- Information Systems top 5%
- Artificial Intelligence top 10%
- Computational Theory and Mathematics top 10%
- Computer Science Applications top 10%
- Molecular Biology
- Co-authors
- Rui HenriquesSara C. MadeiraArlindo L. OliveiraAndreia SilvaAna PaivaCeleste JacintoA.S. BarretoDaniel Serrano
- Topics
- Data Mining Algorithms and Applications (21 papers)Rough Sets and Fuzzy Logic (9 papers)Advanced Database Systems and Queries (7 papers)
- Partner nations
- Portugal
In The Last Decade
Cláudia Antunes
29 papers receiving 217 citations
Peers
Comparison fields: 5 of 68
- Information Systems 112
- Artificial Intelligence 105
- Computational Theory and Mathematics 52
- Computer Science Applications 44
- Molecular Biology 41
Countries citing papers authored by Cláudia Antunes
This map shows the geographic impact of Cláudia Antunes'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 Cláudia Antunes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cláudia Antunes more than expected).
Fields of papers citing papers by Cláudia Antunes
This network shows the impact of papers produced by Cláudia Antunes. 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 Cláudia Antunes. The network helps show where Cláudia Antunes may publish in the future.
Co-authorship network of co-authors of Cláudia Antunes
This figure shows the co-authorship network connecting the top 25 collaborators of Cláudia Antunes. A scholar is included among the top collaborators of Cláudia Antunes 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 Cláudia Antunes. Cláudia Antunes is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 51 | |
| 4 | 10 | |
| 5 | Mining coherent evolution patterns in education through biclustering. | 1 |
| 6 | 14 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | Atuação do fisioterapeuta especialista na saúde da mulher em contexto de centro de saúde | 1 |
| 10 | 1 | |
| 11 | 10 | |
| 12 | 14 | |
| 13 | 20 | |
| 14 | Social Networks Analysis for Quantifying Students' Performance in Teamwork. | 8 |
| 15 | Mining Teaching Behaviors from Pedagogical Surveys | 2 |
| 16 | 3 | |
| 17 | Acquiring Background Knowledge for Intelligent Tutoring Systems. | 24 |
| 18 | 2 | |
| 19 | Onto4AR: a framework for mining association rules | 6 |
| 20 | Mining Patterns Using Relaxations of User Defined Constraints | 2 |
About Cláudia Antunes
Cláudia Antunes is a scholar working on Information Systems, Signal Processing and Computer Science Applications, having authored 32 papers that have together received 239 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (21 papers), Rough Sets and Fuzzy Logic (9 papers) and Advanced Database Systems and Queries (7 papers). The work is most often cited by research in Computer Science Applications (44 citations), Information Systems (112 citations) and Artificial Intelligence (105 citations). Cláudia Antunes has collaborated with scholars based in Portugal. Frequent co-authors include Rui Henriques, Sara C. Madeira, Arlindo L. Oliveira, Andreia Silva, Ana Paiva, Celeste Jacinto, A.S. Barreto, Daniel Serrano, Ana Paula Costa and Paulo Costa. Their work appears in journals such as Pattern Recognition, Journal of the Association for Information Systems and Polymers.
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.