Jorge Ribeiro

901 total citations · 1 hit paper
40 papers, 463 citations indexed

About

Jorge Ribeiro is a scholar working on Artificial Intelligence, Management Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Jorge Ribeiro has authored 40 papers receiving a total of 463 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 5 papers in Management Information Systems and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Jorge Ribeiro's work include Logic, Reasoning, and Knowledge (7 papers), AI-based Problem Solving and Planning (4 papers) and Big Data and Business Intelligence (4 papers). Jorge Ribeiro is often cited by papers focused on Logic, Reasoning, and Knowledge (7 papers), AI-based Problem Solving and Planning (4 papers) and Big Data and Business Intelligence (4 papers). Jorge Ribeiro collaborates with scholars based in Portugal, Spain and Brazil. Jorge Ribeiro's co-authors include Rui Lima, Sara Paiva, Manuel Fernández-Delgado, José Neves, Eva Cernadas, Senén Barro, António Miguel Rosado da Cruz, José Machado, Henrique Vicente and António Abelha and has published in prestigious journals such as SHILAP Revista de lepidopterología, Neural Networks and Journal of the Association for Information Systems.

In The Last Decade

Jorge Ribeiro

33 papers receiving 422 citations

Hit Papers

Robotic Process Automation and Artificial Intelligence in... 2021 2026 2022 2024 2021 50 100 150 200

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jorge Ribeiro Portugal 9 145 112 94 76 33 40 463
Zohaib Jan Australia 10 102 0.7× 117 1.0× 41 0.4× 52 0.7× 52 1.6× 19 443
Kaveh Bastani United States 9 78 0.5× 148 1.3× 56 0.6× 32 0.4× 35 1.1× 10 418
Constantin-Bălă Zamfirescu Romania 11 233 1.6× 58 0.5× 49 0.5× 28 0.4× 56 1.7× 44 461
Emil Blixt Hansen Denmark 6 124 0.9× 41 0.4× 58 0.6× 35 0.5× 39 1.2× 6 308
T. Govindaraj United States 13 180 1.2× 123 1.1× 51 0.5× 58 0.8× 47 1.4× 79 533
Gilbert Owusu United Kingdom 12 87 0.6× 184 1.6× 45 0.5× 24 0.3× 36 1.1× 73 439
Mihnea Alexandru Moisescu Romania 12 127 0.9× 48 0.4× 88 0.9× 80 1.1× 59 1.8× 70 400
Alexis Aubry France 12 189 1.3× 79 0.7× 146 1.6× 71 0.9× 30 0.9× 42 445
Peng Pan China 11 98 0.7× 142 1.3× 57 0.6× 143 1.9× 16 0.5× 23 392

Countries citing papers authored by Jorge Ribeiro

Since Specialization
Citations

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

Fields of papers citing papers by Jorge Ribeiro

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jorge Ribeiro

This figure shows the co-authorship network connecting the top 25 collaborators of Jorge Ribeiro. A scholar is included among the top collaborators of Jorge Ribeiro 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 Jorge Ribeiro. Jorge Ribeiro 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
1.
Costa, André L.H., et al.. (2025). A Contribution of Shortest Paths Algorithms to the NetworkX Python Library. Applied Sciences. 15(15). 8273–8273.
2.
Souza, Lucas Anjos, Débora Barros Barbosa, Jorge Ribeiro, et al.. (2025). Phytochemical Profile, Cytotoxicity, Anti-Inflammatory, Antioxidant, and Antiglycation Activity of Annona crassiflora Extract: An In Vitro Study. Cosmetics. 12(2). 36–36. 2 indexed citations
3.
Ribeiro, Jorge, et al.. (2023). A Gloss Based Translation From European Portuguese to Portuguese Sign Language. 1–4. 1 indexed citations
4.
Ribeiro, Jorge, et al.. (2022). Neural Machine Translation Approach in Automatic Translations between Portuguese Language and Portuguese Sign Language Glosses. 2022 17th Iberian Conference on Information Systems and Technologies (CISTI). 1–7. 3 indexed citations
5.
Ribeiro, Jorge, José Afonso, Miguel Camões, et al.. (2021). Methodological Characteristics, Physiological and Physical Effects, and Future Directions for Combined Training in Soccer: A Systematic Review. Healthcare. 9(8). 1075–1075. 10 indexed citations
7.
Ribeiro, Jorge, et al.. (2020). Effort Estimation in Named Entity Tagging Tasks. Language Resources and Evaluation. 298–306. 1 indexed citations
8.
Ribeiro, Jorge, et al.. (2020). Psychosocial Risks Assessment in Cryopreservation Laboratories. Safety and Health at Work. 11(4). 431–442. 6 indexed citations
9.
Lima, Rui, António Miguel Rosado da Cruz, & Jorge Ribeiro. (2020). Artificial Intelligence Applied to Software Testing: A Literature Review. 1–6. 20 indexed citations
10.
Ribeiro, Jorge, et al.. (2020). Psychosocial risk management. Procedia Computer Science. 176. 743–752.
11.
Ribeiro, Jorge, et al.. (2019). An artificial intelligence case based approach to motivational students assessment in (e)-learning environments. Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT). 1–6. 3 indexed citations
12.
Ribeiro, Jorge, et al.. (2018). Machine Learning Powered Data Platform for High-Quality Speech and NLP Workflows.. Conference of the International Speech Communication Association. 1962–1963. 1 indexed citations
13.
Fernández-Delgado, Manuel, Eva Cernadas, Senén Barro, Jorge Ribeiro, & José Neves. (2013). Direct Kernel Perceptron (DKP): Ultra-fast kernel ELM-based classification with non-iterative closed-form weight calculation. Neural Networks. 50. 60–71. 42 indexed citations
14.
Fernández-Delgado, Manuel, et al.. (2011). Direct Parallel Perceptrons (DPPs): Fast Analytical Calculation of the Parallel Perceptrons Weights With Margin Control for Classification Tasks. IEEE Transactions on Neural Networks. 22(11). 1837–1848. 14 indexed citations
15.
Ribeiro, Jorge, José Machado, António Abelha, Manuel Fernández-Delgado, & José Neves. (2010). Integrating incomplete information into the relational data model. RepositóriUM (Universidade do Minho). 1. 57–62. 1 indexed citations
16.
Ribeiro, Jorge, José Machado, António Abelha, Manuel Fernández-Delgado, & José Neves. (2010). Handling incomplete information in an evolutionary environment. RepositóriUM (Universidade do Minho). 2. 1–8. 2 indexed citations
17.
Ribeiro, Jorge, et al.. (2009). Wine vinification prediction using data mining tools. RepositóriUM (Universidade do Minho). 78–85. 11 indexed citations
18.
Ribeiro, Jorge, et al.. (2009). Service-Oriented Architecture Adoption In A Portuguese Company: A case Study.. Journal of the Association for Information Systems. 48–61. 1 indexed citations
19.
Ribeiro, Jorge, Paulo Nováis, José Neves, & Manuel Fernández-Delgado. (2009). Quality of the information: the application in the winification process in wine production. RepositóriUM (Universidade do Minho). 62–70. 2 indexed citations
20.
Ribeiro, Jorge, et al.. (2009). THE MAIN BENEFITS OF COBIT IN A HIGH PUBLIC EDUCATIONAL INSTITUTION - A CASE STUDY. Journal of the Association for Information Systems. 88. 11 indexed citations

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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