Marcos Da Silveira

631 citations
41 papers · 260 indexed · h-index 8

Marcos Da Silveira

37 papers receiving 242 citations

Peers

Marcos Da Silveira
Comparison fields: 5 of 65
  • Artificial Intelligence 160
  • Molecular Biology 90
  • Information Systems 54
  • Management Science and Operations Research 51
  • Health Information Management 34
Replace Cédric Pruski with:
Cédric Pruski Luxembourg
Sonja Zillner Germany
Gianluca Correndo United Kingdom
Duygu Çelik Ertuğrul Türkiye
Anand Sharma India
Kathrin Dentler Netherlands
Bikash Kanti Sarkar India
Thomas Aden Germany
Giorgio Leonardi Italy
Alessandra Alaniz Macedo Brazil
Marcos Da Silveira relative to Cédric Pruski Luxembourg Cédric Pruski's profile →
Citations per field
00.5×1.5×
Cédric Pruski · 1×
Citations per year

Countries citing papers authored by Marcos Da Silveira

Since Specialization
Citations

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

Fields of papers citing papers by Marcos Da Silveira

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marcos Da Silveira. 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 Marcos Da Silveira. The network helps show where Marcos Da Silveira may publish in the future.

Co-authorship network of co-authors of Marcos Da Silveira

This figure shows the co-authorship network connecting the top 25 collaborators of Marcos Da Silveira. A scholar is included among the top collaborators of Marcos Da Silveira 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 Marcos Da Silveira. Marcos Da Silveira 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
#WorkIndexed citations
1 0
2 1
3 2
4 0
5 2
6 7
7 24
8
Capturing the Relationship between Evolving Biomedical Concepts via Background Knowledge.
2
9
Complaint Ontology Pattern - COP
1
10 7
11 9
12 4
13 62
14 16
15 6
16
Identifying change patterns of concept attributes in ontology evolution
1
17 3
18
Une approche pour la validation du contenu d'une ontologie par un système à base de questions/réponses
1
19 26
20
Protecting Patient Privacy when Sharing Medical Data
6

About Marcos Da Silveira

Marcos Da Silveira is a scholar working on Issues, ethics and legal aspects, Artificial Intelligence and Management Information Systems, having authored 41 papers that have together received 260 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (22 papers), Biomedical Text Mining and Ontologies (21 papers) and Service-Oriented Architecture and Web Services (6 papers). The work is most often cited by research in Health Information Management (34 citations), Artificial Intelligence (160 citations) and Management Science and Operations Research (51 citations). Marcos Da Silveira has collaborated with scholars based in Luxembourg, France and Brazil. Frequent co-authors include Cédric Pruski, Ernesto Expósito, Khalil Drira, Júlio Cesar dos Reis, Annette ten Teije, Frank van Harmelen, Rinke Hoekstra, Edwin Geleijn, Marike van der Leeden and Martijn M. Stuiver. Their work appears in journals such as Knowledge-Based Systems, Future Generation Computer Systems and Journal of Biomedical Informatics.

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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