Ricardo Caferra
- Artificial Intelligence top 10%
- Computational Theory and Mathematics top 10%
- Computer Networks and Communications
- Software
- Management Science and Operations Research
- Co-authors
- Nicolas PeltierAlexander LeitschVincent AravantinosGernot SalzerRachid EchahedStéphane Demri
- Topics
- Logic, programming, and type systems (10 papers)Logic, Reasoning, and Knowledge (10 papers)Semantic Web and Ontologies (4 papers)
- Journals
- International Journal of Intelligent SystemsJournal of Artificial Intelligence ResearchJournal of Automated Reasoning
- Partner nations
- France
In The Last Decade
Ricardo Caferra
12 papers receiving 82 citations
Peers
Comparison fields: 5 of 20
- Artificial Intelligence 100
- Computational Theory and Mathematics 43
- Computer Networks and Communications 21
- Software 20
- Management Science and Operations Research 5
Countries citing papers authored by Ricardo Caferra
This map shows the geographic impact of Ricardo Caferra'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 Ricardo Caferra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ricardo Caferra more than expected).
Fields of papers citing papers by Ricardo Caferra
This network shows the impact of papers produced by Ricardo Caferra. 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 Ricardo Caferra. The network helps show where Ricardo Caferra may publish in the future.
Co-authorship network of co-authors of Ricardo Caferra
This figure shows the co-authorship network connecting the top 25 collaborators of Ricardo Caferra. A scholar is included among the top collaborators of Ricardo Caferra 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 Ricardo Caferra. Ricardo Caferra is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 5 | |
| 3 | 8 | |
| 4 | 2 | |
| 5 | 19 | |
| 6 | 0 | |
| 7 | 5 | |
| 8 | Selected Papers from Automated Deduction in Classical and Non-Classical Logics | 1 |
| 9 | 3 | |
| 10 | 5 | |
| 11 | Extending semantic resolution via automated model building: applications | 10 |
| 12 | 0 | |
| 13 | 15 | |
| 14 | 20 | |
| 15 | Proof analogy in interactive theorem proving: a method to express and use it via second order pattern matching | 9 |
About Ricardo Caferra
Ricardo Caferra is a scholar working on Software, Computational Theory and Mathematics and Artificial Intelligence, having authored 15 papers that have together received 107 indexed citations. Recurring topics across this work include Logic, programming, and type systems (10 papers), Logic, Reasoning, and Knowledge (10 papers) and Semantic Web and Ontologies (4 papers). The work is most often cited by research in Software (20 citations), Artificial Intelligence (100 citations) and Computational Theory and Mathematics (43 citations). Ricardo Caferra has collaborated with scholars based in France. Frequent co-authors include Nicolas Peltier, Alexander Leitsch, Vincent Aravantinos, Gernot Salzer, Rachid Echahed and Stéphane Demri. Their work appears in journals such as International Journal of Intelligent Systems, Journal of Artificial Intelligence Research and Journal of Automated Reasoning.
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.