José Viterbo

1.3k total citations
124 papers, 602 citations indexed

About

José Viterbo is a scholar working on Information Systems, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, José Viterbo has authored 124 papers receiving a total of 602 indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Information Systems, 33 papers in Artificial Intelligence and 32 papers in Computer Networks and Communications. Recurrent topics in José Viterbo's work include Context-Aware Activity Recognition Systems (17 papers), E-Government and Public Services (15 papers) and Big Data and Business Intelligence (10 papers). José Viterbo is often cited by papers focused on Context-Aware Activity Recognition Systems (17 papers), E-Government and Public Services (15 papers) and Big Data and Business Intelligence (10 papers). José Viterbo collaborates with scholars based in Brazil, France and Netherlands. José Viterbo's co-authors include Flávia Bernardini, Cristiano Maciél, Cristina Boeres, Vinod E. F. Rebello, Leandro Miranda, Markus Endler, Daniela Trevisan, Roberto Pereira, Karin Breitman and Marco A. Casanova and has published in prestigious journals such as SHILAP Revista de lepidopterología, Sensors and Pattern Recognition.

In The Last Decade

José Viterbo

104 papers receiving 575 citations

Peers

José Viterbo
Ibrahim Almarashdeh Saudi Arabia
José Viterbo
Citations per year, relative to José Viterbo José Viterbo (= 1×) peers Ibrahim Almarashdeh

Countries citing papers authored by José Viterbo

Since Specialization
Citations

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

Fields of papers citing papers by José Viterbo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of José Viterbo

This figure shows the co-authorship network connecting the top 25 collaborators of José Viterbo. A scholar is included among the top collaborators of José Viterbo 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 José Viterbo. José Viterbo 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.
Viterbo, José, et al.. (2025). Two‐Step Estimation Strategy for Predicting Petroleum Reservoir Simulation Jobs Runtime on an HPC Cluster. Concurrency and Computation Practice and Experience. 37(4-5).
3.
Bernardini, Flávia, et al.. (2024). Exploring Interpretability in Open Government Data with ChatGPT. 186–195. 1 indexed citations
5.
Bernardini, Flávia, et al.. (2023). Machine Learning Applied to Public Transportation by Bus: A Systematic Literature Review. Transportation Research Record Journal of the Transportation Research Board. 2677(7). 639–660. 5 indexed citations
6.
Bernardini, Flávia, et al.. (2023). Hippolyta: a framework to enhance open data interpretability and empower citizens. Research Repository (Delft University of Technology). 191–198. 2 indexed citations
8.
9.
Miranda, Leandro, José Viterbo, & Flávia Bernardini. (2022). A framework for spatial regionalization composed of novel clustering‐based algorithms under spatial contiguity constraints. Transactions in GIS. 26(4). 1775–1800. 2 indexed citations
10.
Viterbo, José, et al.. (2022). A New Approach for Assessing Metadata Completeness in Open Data Portals. International Journal of Electronic Government Research. 18(1). 1–20. 1 indexed citations
11.
Bernardini, Flávia, et al.. (2022). Uso do TAM — Technology Acceptance Model — no Ciclo de Design de Aplicações Computacionais. 3–4. 1 indexed citations
12.
Bernardini, Flávia, et al.. (2022). Unified vocabulary in Official Gazettes: An exploratory study on procurement data. 195–202. 5 indexed citations
13.
Viterbo, José, et al.. (2022). Proposta de uma IDE para desenvolvimento de SMA Embarcados. 49–60. 1 indexed citations
14.
Viterbo, José, et al.. (2022). Adição de Recursos em Tempo de Execução a Sistemas Multi-Agentes Embarcados. 73–84. 1 indexed citations
16.
Bernardini, Flávia, et al.. (2019). Mining direct acyclic graphs to find frequent substructures — An experimental analysis on educational data. Information Sciences. 482. 266–278. 22 indexed citations
17.
Viterbo, José, et al.. (2017). Chapter 3: General Features of Smart City Approaches from Information Systems Perspective and Its Challenges. 2 indexed citations
18.
Viterbo, José, et al.. (2017). Managing Natural Resources in a Smart Bathroom Using a Ubiquitous Multi-Agent System. 101–112. 2 indexed citations
19.
Trevisan, Daniela, et al.. (2015). My Health: An Online Healthcare Social Network Inclusive for Elderly People. Americas Conference on Information Systems. 1 indexed citations
20.
Viterbo, José & Cristiano Maciél. (2013). Workshop sobre aspectos da interação humano-computador para a web social. Human Factors in Computing Systems. 346–347. 1 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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